-------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/vicentevalentim/Dropbox/JOP third submission/JOP replicatio
> n/cabinas_jop_log.smcl
  log type:  smcl
 opened on:  19 Sep 2023, 12:34:42

. 
end of do-file

. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"

. cd "~/Dropbox/JOP third submission/JOP replication/"
/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication

. 
end of do-file

. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/cses2_3.dta, clear
( )

. 
. * Run analyses
. regr like_party pp_dummy, cluster(respondent_code)

Linear regression                               Number of obs     =    755,529
                                                F(1, 132944)      =      85.78
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0001
                                                Root MSE          =     2.9582

                  (Std. err. adjusted for 132,945 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |  -.6012691   .0649205    -9.26   0.000    -.7285121   -.4740262
       _cons |   4.294574    .004367   983.41   0.000     4.286014    4.303133
------------------------------------------------------------------------------

. est store like_party_1

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr like_party pp_dummy if cses_wave == 2, cluster(respondent_code)

Linear regression                               Number of obs     =    300,485
                                                F(1, 59652)       =      56.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0002
                                                Root MSE          =     2.9906

                   (Std. err. adjusted for 59,653 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |  -.6956235   .0925582    -7.52   0.000    -.8770379    -.514209
       _cons |   4.386659   .0063693   688.72   0.000     4.374175    4.399143
------------------------------------------------------------------------------

. est store like_party_2

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr like_party pp_dummy if cses_wave == 3, cluster(respondent_code)

Linear regression                               Number of obs     =    455,044
                                                F(1, 73291)       =      34.92
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0001
                                                Root MSE          =      2.935

                   (Std. err. adjusted for 73,292 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |  -.5383023   .0910883    -5.91   0.000    -.7168351   -.3597695
       _cons |   4.233843   .0058963   718.05   0.000     4.222286    4.245399
------------------------------------------------------------------------------

. est store like_party_3

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr like_party pp_dummy if center_right == 1, cluster(respondent_code)

Linear regression                               Number of obs     =    278,116
                                                F(1, 122079)      =     128.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0005
                                                Root MSE          =     2.9712

                  (Std. err. adjusted for 122,080 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |  -.7358745   .0650194   -11.32   0.000    -.8633114   -.6084375
       _cons |   4.429179   .0069954   633.15   0.000     4.415468     4.44289
------------------------------------------------------------------------------

. est store like_party_4

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. regr like_party pp_dummy if center_right == 1 &  cses_wave == 2, cluster(resp
> ondent_code)

Linear regression                               Number of obs     =    116,993
                                                F(1, 56199)       =      85.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0008
                                                Root MSE          =     2.9843

                   (Std. err. adjusted for 56,200 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   -.857029   .0927229    -9.24   0.000    -1.038766   -.6752914
       _cons |   4.548065   .0107512   423.03   0.000     4.526992    4.569137
------------------------------------------------------------------------------

. est store like_party_5

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. regr like_party pp_dummy if center_right == 1 &  cses_wave == 3, cluster(resp
> ondent_code)

Linear regression                               Number of obs     =    161,123
                                                F(1, 65879)       =      50.40
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0003
                                                Root MSE          =     2.9587

                   (Std. err. adjusted for 65,880 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
  like_party | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |  -.6475394   .0912121    -7.10   0.000    -.8263152   -.4687636
       _cons |    4.34308   .0091995   472.10   0.000     4.325049    4.361111
------------------------------------------------------------------------------

. est store like_party_6

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. * Make table
. esttab like_party_1 like_party_2 like_party_3 like_party_4 like_party_5 like_
> party_6 using 03_tables/table1.tex, tex se replace mtitles ("CSES Waves 2 and
>  3" "CSES Wave 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave
>  3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3") keep(pp_dummy _cons) co
> eflabels (pp_dummy "PP (dummy)" _cons "Constant") s(Sample, label("Sample")) 
> star(* 0.10 ** 0.05 *** 0.01) addnotes("Standard errors are clustered by resp
> ondent") scalars(e(N))
(output written to 03_tables/table1.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/table2.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/cses2_3.dta, clear
( )

. 
. * Run analyses
. regr difference_voter_expert pp_dummy

      Source |       SS           df       MS      Number of obs   =   628,003
-------------+----------------------------------   F(1, 628001)    =    201.34
       Model |  1314.37877         1  1314.37877   Prob > F        =    0.0000
    Residual |  4099714.99   628,001  6.52819819   R-squared       =    0.0003
-------------+----------------------------------   Adj R-squared   =    0.0003
       Total |  4101029.37   628,002  6.53028075   Root MSE        =     2.555

------------------------------------------------------------------------------
difference~t | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .7711658   .0543481    14.19   0.000     .6646454    .8776863
       _cons |   .0088161   .0032299     2.73   0.006     .0024857    .0151466
------------------------------------------------------------------------------

. est store lr_party_1

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr difference_voter_expert pp_dummy if cses_wave == 2, cluster(respondent_c
> ode)

Linear regression                               Number of obs     =    235,726
                                                F(1, 46951)       =     209.22
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0005
                                                Root MSE          =     2.5489

                   (Std. err. adjusted for 46,952 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
difference~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .8237755   .0569516    14.46   0.000     .7121495    .9354015
       _cons |  -.0035806   .0060168    -0.60   0.552    -.0153737    .0082125
------------------------------------------------------------------------------

. est store lr_party_2

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr difference_voter_expert pp_dummy if cses_wave == 3, cluster(respondent_c
> ode)

Linear regression                               Number of obs     =    392,277
                                                F(1, 65187)       =     203.77
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0002
                                                Root MSE          =     2.5587

                   (Std. err. adjusted for 65,188 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
difference~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .7220415   .0505811    14.27   0.000     .6229024    .8211806
       _cons |   .0162505   .0051645     3.15   0.002      .006128     .026373
------------------------------------------------------------------------------

. est store lr_party_3

. estadd local  Sample "All parties"

added macro:
             e(Sample) : "All parties"

. 
. regr difference_voter_expert pp_dummy if center_right == 1, cluster(responden
> t_code)

Linear regression                               Number of obs     =    238,027
                                                F(1, 104322)      =     904.48
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0018
                                                Root MSE          =     2.5867

                  (Std. err. adjusted for 104,323 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
difference~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   1.157762   .0384964    30.07   0.000      1.08231    1.233215
       _cons |  -.3777803   .0068607   -55.06   0.000    -.3912271   -.3643335
------------------------------------------------------------------------------

. est store lr_party_4

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. regr difference_voter_expert pp_dummy if center_right == 1 &  cses_wave == 2,
>  cluster(respondent_code)

Linear regression                               Number of obs     =     95,664
                                                F(1, 45698)       =     357.63
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0022
                                                Root MSE          =     2.5207

                   (Std. err. adjusted for 45,699 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
difference~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   1.085768   .0574145    18.91   0.000     .9732352    1.198302
       _cons |  -.2655736   .0103747   -25.60   0.000    -.2859081   -.2452391
------------------------------------------------------------------------------

. est store lr_party_5

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. regr difference_voter_expert pp_dummy if center_right == 1 &  cses_wave == 3,
>  cluster(respondent_code)

Linear regression                               Number of obs     =    142,363
                                                F(1, 58623)       =     544.22
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0016
                                                Root MSE          =     2.6275

                   (Std. err. adjusted for 58,624 clusters in respondent_code)
------------------------------------------------------------------------------
             |               Robust
difference~t | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   1.191157   .0510599    23.33   0.000     1.091079    1.291234
       _cons |  -.4528646   .0091018   -49.76   0.000    -.4707041   -.4350251
------------------------------------------------------------------------------

. est store lr_party_6

. estadd local  Sample "Center-right parties"

added macro:
             e(Sample) : "Center-right parties"

. 
. * Make table
. esttab lr_party_1 lr_party_2 lr_party_3 lr_party_4 lr_party_5 lr_party_6 usin
> g 03_tables/table2.tex, tex se replace mtitles ("CSES Waves 2 and 3" "CSES Wa
> ve 2" "CSES Wave 3" "CSES Waves 2 and 3" "CSES Wave 2" "CSES Wave 3" "CSES Wa
> ves 2 and 3" "CSES Wave 2" "CSES Wave 3") keep(pp_dummy _cons) coeflabels (pp
> _dummy "PP (dummy)" _cons "Constant") s(Sample, label("Sample")) star(* 0.10 
> ** 0.05 *** 0.01) addnotes("Standard errors are clustered by respondent") sca
> lars(e(N))
(output written to 03_tables/table2.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/table4.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. * Run analyses
. 
. * Model 1
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_ele
> cspecific) cluster(mesa_code_elecspecific)
(dropped 32160 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,474
Absorbing 1 HDFE group                            F(   4,  59236) =   10596.64
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4046
Number of clusters (mesa_code_elecspecific) =     59,237Root MSE  =     5.2282

                  (Std. err. adjusted for 59,237 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.121899    .062844   -97.41   0.000    -6.245074   -5.9
> 98725
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0404565   .0712617     0.57   0.570    -.0992168    .18
> 01298
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.167986   .6933568     1.68   0.092    -.1909961    2.5
> 26968
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.145957   1.121938    -2.80   0.005    -5.344961    -.9
> 46953
                   |
             _cons |   27.43706   .0151892  1806.35   0.000     27.40729    27.
> 46683
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59237       59237           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_pp_ddd

. 
. * Model 2
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) clu
> ster(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,986
Absorbing 1 HDFE group                            F(   4,  76157) =   45033.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8200
                                                  Adj R-squared   =     0.7136
                                                  Within R-sq.    =     0.4234
Number of clusters (mesa_code_elecspecific) =     76,158Root MSE  =     9.4294

                  (Std. err. adjusted for 76,158 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.92846   .0686972  -188.19   0.000     -13.0631   -12.
> 79381
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.027174   .0779292   -13.18   0.000    -1.179914   -.87
> 44326
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4127518   .5894408     0.70   0.484    -.7425492    1.5
> 68053
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.454152   1.008371    -2.43   0.015    -4.430553   -.47
> 77504
                   |
             _cons |   34.61937   .0115142  3006.67   0.000      34.5968    34.
> 64194
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76158       76158           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_pp_ddd

. 
. * Model 3
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspec
> ific) cluster(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,986
Absorbing 1 HDFE group                            F(   5,  76157) =   52208.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9147
                                                  Adj R-squared   =     0.8643
                                                  Within R-sq.    =     0.7267
Number of clusters (mesa_code_elecspecific) =     76,158Root MSE  =     6.4917

                  (Std. err. adjusted for 76,158 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.32835   .0738505  -275.26   0.000     -20.4731   -20.
> 18361
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2106771   .0751797     2.80   0.005     .0633253    .35
> 80289
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7924392   .5892418     1.34   0.179     -.362472     1.
> 94735
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.692002   1.008169    -3.66   0.000    -5.668008   -1.7
> 15997
                   |
            period |
                2  |  -14.04042   .0365116  -384.55   0.000    -14.11198   -13.
> 96885
                3  |          0  (omitted)
                   |
             _cons |   41.23033   .0235892  1747.85   0.000      41.1841    41.
> 27657
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76158       76158           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_pp_ddd

. 
. * Placebo
. reghdfe pp_voteshare_lag post##ep##ciutadella, absorb(mesa_code_elecspecific)
>  cluster(mesa_code_elecspecific)
(dropped 23221 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    105,890
Absorbing 1 HDFE group                            F(   4,  52944) =   32096.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9349
                                                  Adj R-squared   =     0.8698
                                                  Within R-sq.    =     0.6984
Number of clusters (mesa_code_elecspecific) =     52,945Root MSE  =     6.4978

                  (Std. err. adjusted for 52,945 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
  pp_voteshare_lag | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -14.09829   .0809325  -174.20   0.000    -14.25692   -13.
> 93966
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1718456   .0924712     1.86   0.063    -.0093989      .
> 35309
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -1.025296   .5664412    -1.81   0.070    -2.135526    .08
> 49338
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -.9234955   .9922132    -0.93   0.352    -2.868242    1.0
> 21251
                   |
             _cons |   41.33486   .0199681  2070.04   0.000     41.29572    41.
> 37399
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     52945       52945           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store placebo_pp_ddd

. 
. * Make table
. esttab twoperiods_pp_ddd prepost_pp_ddd threeperiods_pp_ddd placebo_pp_ddd us
> ing 03_tables/table4.tex, tex se replace mtitles ("2014-2019" "2009-2019" "20
> 09-2019" "Placebo lagged outcome")  keep (1.post 1.post#1.ep 1.post#1.ciutade
> lla 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.p
> ost#1.ep "EP election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.pos
> t#1.ep#1.ciutadella "EP 2019 x Ciutadella" 2.period "2014-2015 election") sta
> r(* 0.10 ** 0.05 *** 0.01) addnotes("All models include voting station * elec
> tion type fixed effects" "Standard errors are clustered by voting station * e
> lection type") 
(output written to 03_tables/table4.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/table5.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. use 01_data/cis_data.dta, clear

. 
. * Run analyses
. 
. regr cabine_use pp_dummy, r

Linear regression                               Number of obs     =      1,847
                                                F(1, 1845)        =      11.55
                                                Prob > F          =     0.0007
                                                R-squared         =     0.0063
                                                Root MSE          =     .49543

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |    .113812   .0334868     3.40   0.001      .048136    .1794881
       _cons |    .427044   .0124118    34.41   0.000     .4027014    .4513866
------------------------------------------------------------------------------

. est store pp_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local FE "No"

added macro:
                 e(FE) : "No"

. 
. regr cabine_use pp_dummy i.CCAA, r

Linear regression                               Number of obs     =      1,847
                                                F(19, 1827)       =      45.56
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2140
                                                Root MSE          =     .44278

-------------------------------------------------------------------------------
----------------
                              |               Robust
                   cabine_use | Coefficient  std. err.      t    P>|t|     [95%
>  con                                                                         
>     f. interval]
------------------------------+------------------------------------------------
----------------
                     pp_dummy |   .0620417   .0301818     2.06   0.040     .002
> 8473                                                                         
>         .1212361
                              |
                         CCAA |
                      Aragón  |  -.0897035   .0645425    -1.39   0.165    -.216
> 2884                                                                         
>         .0368813
    Asturias (Principado de)  |  -.2223241   .0662738    -3.35   0.001    -.352
> 3045                                                                         
>        -.0923437
             Balears (Illes)  |  -.1321739   .0631238    -2.09   0.036    -.255
> 9764                                                                         
>        -.0083715
                    Canarias  |   .3790184   .0477885     7.93   0.000     .285
> 2926                                                                         
>         .4727441
                   Cantabria  |   .0189394   .0632698     0.30   0.765    -.105
> 1493                                                                         
>         .1430282
          Castilla-La Mancha  |   .0812481   .0671631     1.21   0.227    -.050
> 4765                                                                         
>         .2129726
             Castilla y León  |   .0503454    .063747     0.79   0.430    -.074
> 6792                                                                         
>           .17537
                    Cataluña  |  -.4494289   .0345086   -13.02   0.000    -.517
> 1093                                                                         
>        -.3817484
        Comunitat Valenciana  |  -.0716436   .0512482    -1.40   0.162    -.172
> 1548                                                                         
>         .0288675
                 Extremadura  |   .2120628    .057937     3.66   0.000     .098
> 4332                                                                         
>         .3256924
                     Galicia  |  -.0268084   .0629393    -0.43   0.670     -.15
> 0249                                                                         
>         .0966322
       Madrid (Comunidad de)  |  -.4184945   .0369599   -11.32   0.000    -.490
> 9827                                                                         
>        -.3460064
          Murcia (Región de)  |   .1267141   .0616841     2.05   0.040     .005
> 7354                                                                         
>         .2476929
Navarra (Comunidad Foral de)  |  -.0769993   .0839086    -0.92   0.359    -.241
> 5662                                                                         
>         .0875676
                  País Vasco  |  -.0916946   .0718691    -1.28   0.202    -.232
> 6487                                                                         
>         .0492596
                  Rioja (La)  |   .0601875   .0697591     0.86   0.388    -.076
> 6285                                                                         
>         .1970034
  Ceuta (Ciudad Autónoma de)  |   .3058338   .0656224     4.66   0.000     .177
> 1309                                                                         
>         .4345367
Melilla (Ciudad Autónoma de)  |   .1487341   .1142908     1.30   0.193    -.075
> 4203                                                                         
>         .3728884
                              |
                        _cons |   .5389007   .0296552    18.17   0.000     .480
> 7391                                                                         
>         .5970624
-------------------------------------------------------------------------------
----------------

. est store pp_fe

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local  FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,356
                                                F(25, 1330)       =      16.73
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1167
                                                Root MSE          =     .47399

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1314563     .03732     3.52   0.000     .0
> 582438                                                                       
>           .2046687
                         female |  -.0158409   .0277424    -0.57   0.568    -.0
> 702646                                                                       
>           .0385828
                                |
                         income |
         Menos o igual a 300 €  |   .0380048    .091719     0.41   0.679    -.1
> 419248                                                                       
>           .2179343
                De 301 a 600 €  |   .0014734   .0589043     0.03   0.980    -.1
> 140822                                                                       
>           .1170289
                De 601 a 900 €  |  -.0255149   .0484068    -0.53   0.598     -.
> 120477                                                                       
>           .0694471
              De 901 a 1.200 €  |  -.0573133   .0460066    -1.25   0.213    -.1
> 475668                                                                       
>           .0329402
            De 1.201 a 1.800 €  |  -.0589429   .0480938    -1.23   0.221    -.1
> 532908                                                                       
>           .0354051
            De 1.801 a 2.400 €  |  -.0387394   .0584283    -0.66   0.507    -.1
> 533611                                                                       
>           .0758823
            De 2.401 a 3.000 €  |  -.1229924   .0799346    -1.54   0.124    -.2
> 798039                                                                       
>           .0338192
            De 3.001 a 4.500 €  |   .0919186   .1104933     0.83   0.406    -.1
> 248416                                                                       
>           .3086788
            De 4.501 a 6.000 €  |  -.4973995   .0736127    -6.76   0.000    -.6
> 418091                                                                       
>          -.3529898
                Más de 6.000 €  |  -.0920014   .2522237    -0.36   0.715    -.5
> 868011                                                                       
>           .4027984
                                |
                            age |   .0026836   .0047772     0.56   0.574     -.
> 006688                                                                       
>           .0120553
                         age_sq |  -.0000539   .0000491    -1.10   0.273    -.0
> 001502                                                                       
>           .0000425
                                |
                      education |
                      Primaria  |  -.0652387   .1148669    -0.57   0.570    -.2
> 905788                                                                       
>           .1601014
           Secundaria 1ª etapa  |  -.1616461   .1148042    -1.41   0.159    -.3
> 868633                                                                       
>            .063571
           Secundaria 2ª etapa  |  -.2292419    .116196    -1.97   0.049    -.4
> 571894                                                                       
>          -.0012945
                          F.P.  |  -.1206527   .1155289    -1.04   0.297    -.3
> 472915                                                                       
>            .105986
                    Superiores  |  -.1323317   .1169844    -1.13   0.258    -.3
> 618258                                                                       
>           .0971625
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .010783   .0626476     0.17   0.863    -.1
> 121159                                                                       
>           .1336818
    10.001 a 50.000 habitantes  |  -.1260727   .0601022    -2.10   0.036    -.2
> 439782                                                                       
>          -.0081672
   50.001 a 100.000 habitantes  |  -.1207442   .0638278    -1.89   0.059    -.2
> 459584                                                                       
>             .00447
  100.001 a 400.000 habitantes  |  -.2403321   .0610222    -3.94   0.000    -.3
> 600423                                                                       
>          -.1206219
400.001 a 1.000.000 habitantes  |  -.3231655    .066451    -4.86   0.000    -.4
> 535258                                                                       
>          -.1928053
   Más de 1.000.000 habitantes  |  -.5614998   .0605895    -9.27   0.000    -.6
> 803613                                                                       
>          -.4426384
                                |
                          _cons |   .8184492   .1545058     5.30   0.000     .5
> 153476                                                                       
>           1.121551
-------------------------------------------------------------------------------
------------------

. est store pp_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local  FE "No"

added macro:
                 e(FE) : "No"

. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.TAMUNI i.CC
> AA, r

Linear regression                               Number of obs     =      1,356
                                                F(43, 1312)       =      19.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2489
                                                Root MSE          =     .44009

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0964548    .034805     2.77   0.006     .0
> 281752                                                                       
>           .1647344
                         female |  -.0158589   .0259646    -0.61   0.541    -.0
> 667955                                                                       
>           .0350777
                                |
                         income |
         Menos o igual a 300 €  |  -.0016742   .0902907    -0.02   0.985    -.1
> 788041                                                                       
>           .1754556
                De 301 a 600 €  |  -.0003704   .0564329    -0.01   0.995     -.
> 111079                                                                       
>           .1103383
                De 601 a 900 €  |  -.0328661   .0446197    -0.74   0.462    -.1
> 203999                                                                       
>           .0546678
              De 901 a 1.200 €  |  -.0447737   .0423701    -1.06   0.291    -.1
> 278942                                                                       
>           .0383468
            De 1.201 a 1.800 €  |  -.0222695   .0447873    -0.50   0.619    -.1
> 101321                                                                       
>           .0655931
            De 1.801 a 2.400 €  |   .0051982   .0532411     0.10   0.922    -.0
> 992488                                                                       
>           .1096452
            De 2.401 a 3.000 €  |   -.031228   .0729213    -0.43   0.669    -.1
> 742832                                                                       
>           .1118271
            De 3.001 a 4.500 €  |   .1507493   .1097734     1.37   0.170    -.0
> 646013                                                                       
>           .3660999
            De 4.501 a 6.000 €  |  -.4246083   .1784413    -2.38   0.017    -.7
> 746697                                                                       
>          -.0745469
                Más de 6.000 €  |   .0249654   .2107723     0.12   0.906    -.3
> 885222                                                                       
>            .438453
                                |
                            age |  -.0005947   .0045271    -0.13   0.896    -.0
> 094758                                                                       
>           .0082863
                         age_sq |  -.0000169   .0000471    -0.36   0.721    -.0
> 001093                                                                       
>           .0000756
                                |
                      education |
                      Primaria  |   -.059104   .1052495    -0.56   0.575    -.2
> 655796                                                                       
>           .1473716
           Secundaria 1ª etapa  |  -.1375116   .1062387    -1.29   0.196     -.
> 345928                                                                       
>           .0709047
           Secundaria 2ª etapa  |  -.1661299   .1078428    -1.54   0.124    -.3
> 776931                                                                       
>           .0454333
                          F.P.  |  -.0875001   .1070706    -0.82   0.414    -.2
> 975484                                                                       
>           .1225482
                    Superiores  |  -.1033959   .1084668    -0.95   0.341    -.3
> 161832                                                                       
>           .1093914
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0033695   .0596457     0.06   0.955    -.1
> 136417                                                                       
>           .1203808
    10.001 a 50.000 habitantes  |  -.1291564   .0580572    -2.22   0.026    -.2
> 430516                                                                       
>          -.0152613
   50.001 a 100.000 habitantes  |   -.178349   .0643775    -2.77   0.006    -.3
> 046432                                                                       
>          -.0520549
  100.001 a 400.000 habitantes  |  -.2205494   .0598171    -3.69   0.000     -.
> 337897                                                                       
>          -.1032019
400.001 a 1.000.000 habitantes  |  -.3846467   .0678911    -5.67   0.000    -.5
> 178336                                                                       
>          -.2514597
   Más de 1.000.000 habitantes  |  -.2415861   .0637553    -3.79   0.000    -.3
> 666595                                                                       
>          -.1165126
                                |
                           CCAA |
                        Aragón  |  -.0226734   .0689708    -0.33   0.742    -.1
> 579785                                                                       
>           .1126316
      Asturias (Principado de)  |  -.2286187   .0725652    -3.15   0.002    -.3
> 709752                                                                       
>          -.0862623
               Balears (Illes)  |  -.1856912   .0777969    -2.39   0.017    -.3
> 383112                                                                       
>          -.0330712
                      Canarias  |   .3649967   .0540274     6.76   0.000     .2
> 590073                                                                       
>           .4709862
                     Cantabria  |  -.0635752   .0685943    -0.93   0.354    -.1
> 981417                                                                       
>           .0709913
            Castilla-La Mancha  |   .0021085   .0709689     0.03   0.976    -.1
> 371164                                                                       
>           .1413334
               Castilla y León  |   .0432351   .0712294     0.61   0.544    -.0
> 965009                                                                       
>           .1829711
                      Cataluña  |  -.4435767   .0482151    -9.20   0.000    -.5
> 381638                                                                       
>          -.3489896
          Comunitat Valenciana  |  -.0822272   .0544457    -1.51   0.131    -.1
> 890373                                                                       
>            .024583
                   Extremadura  |   .1502587   .0611434     2.46   0.014     .0
> 303092                                                                       
>           .2702083
                       Galicia  |   -.032892   .0721875    -0.46   0.649    -.1
> 745075                                                                       
>           .1087235
         Madrid (Comunidad de)  |  -.3992227   .0472507    -8.45   0.000    -.4
> 919179                                                                       
>          -.3065274
            Murcia (Región de)  |   .1322366     .06634     1.99   0.046     .0
> 020926                                                                       
>           .2623806
  Navarra (Comunidad Foral de)  |  -.2071578   .0911346    -2.27   0.023    -.3
> 859432                                                                       
>          -.0283724
                    País Vasco  |  -.1208546    .089043    -1.36   0.175    -.2
> 955369                                                                       
>           .0538276
                    Rioja (La)  |  -.0737973    .106031    -0.70   0.487    -.2
> 818061                                                                       
>           .1342115
    Ceuta (Ciudad Autónoma de)  |   .2558526   .0872685     2.93   0.003     .0
> 846515                                                                       
>           .4270537
  Melilla (Ciudad Autónoma de)  |   .1292538   .1152942     1.12   0.262    -.0
> 969273                                                                       
>            .355435
                                |
                          _cons |   .9234004   .1457423     6.34   0.000      .
> 637487                                                                       
>           1.209314
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local  FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. * Make table 
. esttab pp_nocontrols pp_fe pp_controls pp_fe_controls using 03_tables/table5.
> tex, tex se replace keep(pp_dummy) coeflabels (pp_dummy "PP voter (dummy)") n
> omtitles star(* 0.10 ** 0.05 *** 0.01) s(Controls FE, label("Controls" "Regio
> n fixed effects")) addnotes("Standard errors are robust" "The outcome variabl
> e is a dummy for whether each respondent used a private" "voting booth to cas
> t their vote in the general election of November 2019" "Models 2 and 4 includ
> e controls for income, education, age, age squared, size of" "respondent's mu
> nicipality, and a dummy for respondents identifying as female") scalars(e(N))
(output written to 03_tables/table5.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/table6.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/cis_data.dta, clear

. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
(2,957 missing values generated)

. 
. * Run analyses
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy, r

Linear regression                               Number of obs     =      1,847
                                                F(3, 1843)        =       2.18
                                                Prob > F          =     0.0890
                                                R-squared         =     0.0049
                                                Root MSE          =     .30267

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0093021   .0150025    -0.62   0.535    -.0387258    .0
> 201216
           pp_dummy |  -.0258144   .0264424    -0.98   0.329    -.0776746    .0
> 260458
cabine_use_pp_dummy |   .1056928   .0430507     2.46   0.014     .0212595    .1
> 901261
              _cons |   .1020856   .0100418    10.17   0.000     .0823911    .1
> 217801
-------------------------------------------------------------------------------
------

. est store uncomf_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local FE "No"

added macro:
                 e(FE) : "No"

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.CCAA, r

Linear regression                               Number of obs     =      1,847
                                                F(21, 1825)       =       3.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0376
                                                Root MSE          =     .29912

-------------------------------------------------------------------------------
----------------
                              |               Robust
                uncomfortable | Coefficient  std. err.      t    P>|t|     [95%
>  con                                                                         
>     f. interval]
------------------------------+------------------------------------------------
----------------
                   cabine_use |  -.0137941   .0163418    -0.84   0.399    -.045
> 8448                                                                         
>         .0182566
                     pp_dummy |  -.0370522   .0270462    -1.37   0.171    -.090
> 0969                                                                         
>         .0159926
          cabine_use_pp_dummy |   .1051536   .0422713     2.49   0.013     .022
> 2485                                                                         
>         .1880588
                              |
                         CCAA |
                      Aragón  |  -.0284776   .0389599    -0.73   0.465    -.104
> 8884                                                                         
>         .0479331
    Asturias (Principado de)  |   .0876985   .0553588     1.58   0.113    -.020
> 8747                                                                         
>         .1962717
             Balears (Illes)  |    .007329   .0424858     0.17   0.863    -.075
> 9969                                                                         
>          .090655
                    Canarias  |  -.0573965   .0389692    -1.47   0.141    -.133
> 8253                                                                         
>         .0190324
                   Cantabria  |  -.0320745    .037469    -0.86   0.392    -.105
> 5612                                                                         
>         .0414122
          Castilla-La Mancha  |   .1265929   .0577189     2.19   0.028     .013
> 3908                                                                         
>         .2397949
             Castilla y León  |   .0904875   .0509775     1.78   0.076    -.009
> 4928                                                                         
>         .1904678
                    Cataluña  |  -.0579057   .0258834    -2.24   0.025      -.1
> 0867                                                                         
>        -.0071415
        Comunitat Valenciana  |   -.086384   .0249477    -3.46   0.001    -.135
> 3131                                                                         
>        -.0374549
                 Extremadura  |  -.0284337    .040444    -0.70   0.482    -.107
> 7552                                                                         
>         .0508877
                     Galicia  |  -.0552346   .0328336    -1.68   0.093    -.119
> 6299                                                                         
>         .0091608
       Madrid (Comunidad de)  |     -.0034   .0298429    -0.11   0.909    -.061
> 9298                                                                         
>         .0551298
          Murcia (Región de)  |  -.1102939    .023943    -4.61   0.000    -.157
> 2524                                                                         
>        -.0633353
Navarra (Comunidad Foral de)  |   .0287113   .0589705     0.49   0.626    -.086
> 9455                                                                         
>         .1443682
                  País Vasco  |  -.0854341   .0310725    -2.75   0.006    -.146
> 3756                                                                         
>        -.0244926
                  Rioja (La)  |   -.040114   .0402575    -1.00   0.319    -.119
> 0697                                                                         
>         .0388417
  Ceuta (Ciudad Autónoma de)  |   .0447056   .0664893     0.67   0.501    -.085
> 6976                                                                         
>         .1751087
Melilla (Ciudad Autónoma de)  |    -.07021   .0622005    -1.13   0.259    -.192
> 2016                                                                         
>         .0517815
                              |
                        _cons |   .1249262   .0218889     5.71   0.000     .081
> 9964                                                                         
>         .1678561
-------------------------------------------------------------------------------
----------------

. est store uncomf_fe

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.
> TAMUNI age age_sq i.education, r

Linear regression                               Number of obs     =      1,356
                                                F(27, 1328)       =       2.86
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0367
                                                Root MSE          =     .28379

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0337134    .016701    -2.02   0.044    -.0
> 664767                                                                       
>          -.0009501
                       pp_dummy |  -.0365706   .0297247    -1.23   0.219    -.0
> 948831                                                                       
>            .021742
            cabine_use_pp_dummy |   .1175523   .0479617     2.45   0.014     .0
> 234633                                                                       
>           .2116413
                         female |   .0290122   .0159768     1.82   0.070    -.0
> 023303                                                                       
>           .0603548
                                |
                         income |
         Menos o igual a 300 €  |   .0298092   .0634945     0.47   0.639    -.0
> 947513                                                                       
>           .1543697
                De 301 a 600 €  |   .0679181   .0413665     1.64   0.101    -.0
> 132327                                                                       
>            .149069
                De 601 a 900 €  |   .0057013   .0306162     0.19   0.852    -.0
> 543601                                                                       
>           .0657626
              De 901 a 1.200 €  |   .0134649   .0291278     0.46   0.644    -.0
> 436767                                                                       
>           .0706064
            De 1.201 a 1.800 €  |   .0116287   .0276334     0.42   0.674    -.0
> 425811                                                                       
>           .0658385
            De 1.801 a 2.400 €  |  -.0367435   .0289269    -1.27   0.204     -.
> 093491                                                                       
>           .0200039
            De 2.401 a 3.000 €  |  -.0149316   .0425222    -0.35   0.726    -.0
> 983496                                                                       
>           .0684864
            De 3.001 a 4.500 €  |   .0666733   .0706049     0.94   0.345    -.0
> 718361                                                                       
>           .2051826
            De 4.501 a 6.000 €  |  -.0853735   .0336113    -2.54   0.011    -.1
> 513105                                                                       
>          -.0194365
                Más de 6.000 €  |      -.073   .0327401    -2.23   0.026    -.1
> 372279                                                                       
>          -.0087721
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0599538   .0376189     1.59   0.111    -.0
> 138451                                                                       
>           .1337528
    10.001 a 50.000 habitantes  |   .0172546   .0325386     0.53   0.596    -.0
> 465781                                                                       
>           .0810873
   50.001 a 100.000 habitantes  |    .036592   .0366081     1.00   0.318     -.
> 035224                                                                       
>           .1084081
  100.001 a 400.000 habitantes  |   .0035241   .0329026     0.11   0.915    -.0
> 610226                                                                       
>           .0680708
400.001 a 1.000.000 habitantes  |  -.0506184   .0321956    -1.57   0.116    -.1
> 137782                                                                       
>           .0125414
   Más de 1.000.000 habitantes  |  -.0459084   .0362575    -1.27   0.206    -.1
> 170366                                                                       
>           .0252198
                                |
                            age |  -.0021341   .0031694    -0.67   0.501    -.0
> 083518                                                                       
>           .0040835
                         age_sq |   .0000251   .0000336     0.75   0.454    -.0
> 000407                                                                       
>           .0000909
                                |
                      education |
                      Primaria  |  -.0870528   .0905141    -0.96   0.336     -.
> 264619                                                                       
>           .0905134
           Secundaria 1ª etapa  |  -.0517586   .0917094    -0.56   0.573    -.2
> 316697                                                                       
>           .1281524
           Secundaria 2ª etapa  |  -.0982894   .0920835    -1.07   0.286    -.2
> 789343                                                                       
>           .0823555
                          F.P.  |  -.0911509   .0916408    -0.99   0.320    -.2
> 709273                                                                       
>           .0886256
                    Superiores  |  -.0850111   .0919742    -0.92   0.356    -.2
> 654417                                                                       
>           .0954196
                                |
                          _cons |   .1876158   .1073685     1.75   0.081    -.0
> 230146                                                                       
>           .3982461
-------------------------------------------------------------------------------
------------------

. est store uncomf_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local FE "No"

added macro:
                 e(FE) : "No"

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.
> TAMUNI age age_sq i.education i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(45, 1310)       =       2.31
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0768
                                                Root MSE          =     .27971

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0161885   .0174219    -0.93   0.353    -.0
> 503663                                                                       
>           .0179893
                       pp_dummy |  -.0391079   .0296057    -1.32   0.187    -.0
> 971876                                                                       
>           .0189718
            cabine_use_pp_dummy |   .1070496   .0459618     2.33   0.020     .0
> 168827                                                                       
>           .1972165
                         female |   .0286614   .0157818     1.82   0.070    -.0
> 022989                                                                       
>           .0596217
                                |
                         income |
         Menos o igual a 300 €  |   .0252418   .0637596     0.40   0.692    -.0
> 998403                                                                       
>            .150324
                De 301 a 600 €  |   .0809688   .0406164     1.99   0.046     .0
> 012885                                                                       
>           .1606491
                De 601 a 900 €  |   .0097233   .0303799     0.32   0.749    -.0
> 498753                                                                       
>            .069322
              De 901 a 1.200 €  |   .0111537   .0281572     0.40   0.692    -.0
> 440845                                                                       
>           .0663919
            De 1.201 a 1.800 €  |   .0064156   .0278816     0.23   0.818    -.0
> 482818                                                                       
>            .061113
            De 1.801 a 2.400 €  |  -.0375557   .0301565    -1.25   0.213    -.0
> 967161                                                                       
>           .0216047
            De 2.401 a 3.000 €  |  -.0266351   .0424242    -0.63   0.530    -.1
> 098619                                                                       
>           .0565918
            De 3.001 a 4.500 €  |   .0615274    .067269     0.91   0.361    -.0
> 704392                                                                       
>           .1934941
            De 4.501 a 6.000 €  |  -.0770483   .0470606    -1.64   0.102    -.1
> 693707                                                                       
>           .0152742
                Más de 6.000 €  |   -.075425   .0420327    -1.79   0.073    -.1
> 578838                                                                       
>           .0070338
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0546482   .0370362     1.48   0.140    -.0
> 180085                                                                       
>           .1273049
    10.001 a 50.000 habitantes  |   .0194887      .0327     0.60   0.551    -.0
> 446615                                                                       
>           .0836388
   50.001 a 100.000 habitantes  |   .0053875    .037727     0.14   0.886    -.0
> 686244                                                                       
>           .0793994
  100.001 a 400.000 habitantes  |    -.00761   .0338595    -0.22   0.822    -.0
> 740347                                                                       
>           .0588147
400.001 a 1.000.000 habitantes  |  -.0393001   .0361273    -1.09   0.277    -.1
> 101737                                                                       
>           .0315735
   Más de 1.000.000 habitantes  |  -.1047177   .0427722    -2.45   0.014    -.1
> 886272                                                                       
>          -.0208082
                                |
                            age |  -.0011097   .0031349    -0.35   0.723    -.0
> 072596                                                                       
>           .0050402
                         age_sq |   .0000159   .0000332     0.48   0.633    -.0
> 000493                                                                       
>            .000081
                                |
                      education |
                      Primaria  |  -.0806284   .0923209    -0.87   0.383    -.2
> 617413                                                                       
>           .1004846
           Secundaria 1ª etapa  |  -.0439123   .0945747    -0.46   0.643    -.2
> 294467                                                                       
>            .141622
           Secundaria 2ª etapa  |  -.0905356   .0949785    -0.95   0.341    -.2
> 768623                                                                       
>            .095791
                          F.P.  |  -.0804828   .0944429    -0.85   0.394    -.2
> 657586                                                                       
>           .1047931
                    Superiores  |  -.0753385   .0950458    -0.79   0.428    -.2
> 617972                                                                       
>           .1111201
                                |
                           CCAA |
                        Aragón  |   -.022042   .0356966    -0.62   0.537    -.0
> 920707                                                                       
>           .0479867
      Asturias (Principado de)  |   .0561672   .0542064     1.04   0.300    -.0
> 501736                                                                       
>            .162508
               Balears (Illes)  |   .0525638   .0516608     1.02   0.309    -.0
> 487832                                                                       
>           .1539107
                      Canarias  |  -.0624198   .0343576    -1.82   0.069    -.1
> 298216                                                                       
>           .0049821
                     Cantabria  |  -.0356421   .0365304    -0.98   0.329    -.1
> 073065                                                                       
>           .0360222
            Castilla-La Mancha  |   .1264314   .0597288     2.12   0.034     .0
> 092569                                                                       
>           .2436059
               Castilla y León  |   .0845255   .0553489     1.53   0.127    -.0
> 240567                                                                       
>           .1931077
                      Cataluña  |   .0088615   .0351612     0.25   0.801    -.0
> 601169                                                                       
>           .0778398
          Comunitat Valenciana  |  -.0548639   .0275883    -1.99   0.047     -.
> 108986                                                                       
>          -.0007418
                   Extremadura  |  -.0206756   .0432684    -0.48   0.633    -.1
> 055586                                                                       
>           .0642074
                       Galicia  |  -.0932758   .0285169    -3.27   0.001    -.1
> 492196                                                                       
>          -.0373319
         Madrid (Comunidad de)  |   .0972986   .0414976     2.34   0.019     .0
> 158896                                                                       
>           .1787075
            Murcia (Región de)  |  -.0643376   .0246891    -2.61   0.009    -.1
> 127721                                                                       
>           -.015903
  Navarra (Comunidad Foral de)  |  -.0161522   .0558138    -0.29   0.772    -.1
> 256463                                                                       
>           .0933419
                    País Vasco  |  -.0604004   .0362028    -1.67   0.095    -.1
> 314222                                                                       
>           .0106213
                    Rioja (La)  |  -.0909534   .0257658    -3.53   0.000    -.1
> 415002                                                                       
>          -.0404066
    Ceuta (Ciudad Autónoma de)  |   .0927365   .0812046     1.14   0.254    -.0
> 665686                                                                       
>           .2520417
  Melilla (Ciudad Autónoma de)  |  -.0324908   .0644684    -0.50   0.614    -.1
> 589634                                                                       
>           .0939819
                                |
                          _cons |   .1535666   .1106493     1.39   0.165    -.0
> 635025                                                                       
>           .3706358
-------------------------------------------------------------------------------
------------------

. est store uncomf_fe_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. * Make table
. esttab uncomf_nocontrols uncomf_controls uncomf_fe uncomf_fe_controls using 0
> 3_tables/table6.tex, tex se replace  keep (cabine_use pp_dummy cabine_use_pp_
> dummy) coeflabels (cabine_use "Used a booth to vote" pp_dummy "Voted for PP" 
> cabine_use_pp_dummy "Used booth x voted PP") star(* 0.10 ** 0.05 *** 0.01) s(
> Controls FE, label("Controls" "Region fixed effects")) nomtitles addnotes("St
> andard errors are robust" "The outcome variable is a dummy for whether each r
> espondent showed" "signs of discomfort during the survey interview" "Models 2
>  and 4 include controls for income, education, age, age squared, size of" "re
> spondent's municipality, and a dummy for respondents identifying as female") 
> scalars(e(N))
(output written to 03_tables/table6.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. * Run analyses
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (turnout_above_medi
> an_p3 == 1 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cl
> uster(mesa_code_elecspecific)
(dropped 32160 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,418
Absorbing 1 HDFE group                            F(   4,  59208) =   10641.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8748
                                                  Within R-sq.    =     0.4046
Number of clusters (mesa_code_elecspecific) =     59,209Root MSE  =     5.2288

                  (Std. err. adjusted for 59,209 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.121899    .062844   -97.41   0.000    -6.245074   -5.9
> 98725
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0404565   .0712617     0.57   0.570    -.0992168    .18
> 01298
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4519787   .8647178     0.52   0.601    -1.242872    2.1
> 46829
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -4.487034   1.060013    -4.23   0.000    -6.564663   -2.4
> 09405
                   |
             _cons |   27.43796   .0151946  1805.77   0.000     27.40818    27.
> 46774
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59209       59209           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_1

. 
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (turnout_above_medi
> an_p3 == 0 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cl
> uster(mesa_code_elecspecific)
(dropped 32160 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,418
Absorbing 1 HDFE group                            F(   4,  59208) =   10571.22
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4044
Number of clusters (mesa_code_elecspecific) =     59,209Root MSE  =     5.2291

                  (Std. err. adjusted for 59,209 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.121899    .062844   -97.41   0.000    -6.245074   -5.9
> 98725
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0404565   .0712617     0.57   0.570    -.0992168    .18
> 01298
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.883993   1.045991     1.80   0.072    -.1661532     3.
> 93414
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -1.80488   1.795387    -1.01   0.315    -5.323845    1.7
> 14086
                   |
             _cons |   27.43593   .0151956  1805.52   0.000     27.40615    27.
> 46572
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59209       59209           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_2

. 
. reghdfe pp_voteshare post##ep##ciutadella if (turnout_above_median_p3 == 1 | 
> turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_co
> de_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,902
Absorbing 1 HDFE group                            F(   4,  76129) =   45154.40
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8201
                                                  Adj R-squared   =     0.7137
                                                  Within R-sq.    =     0.4234
Number of clusters (mesa_code_elecspecific) =     76,130Root MSE  =     9.4296

                  (Std. err. adjusted for 76,130 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.92846   .0686972  -188.19   0.000     -13.0631   -12.
> 79381
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.027174   .0779292   -13.18   0.000    -1.179914   -.87
> 44326
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .3717993   .7393254     0.50   0.615    -1.077275    1.8
> 20873
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.767779   .9162231    -4.11   0.000    -5.563572   -1.9
> 71986
                   |
             _cons |   34.61964   .0115182  3005.63   0.000     34.59706    34.
> 64221
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76130       76130           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_3

. 
. reghdfe pp_voteshare post##ep##ciutadella if (turnout_above_median_p3 == 0 | 
> turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) cluster(mesa_co
> de_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,902
Absorbing 1 HDFE group                            F(   4,  76129) =   44895.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8201
                                                  Adj R-squared   =     0.7137
                                                  Within R-sq.    =     0.4233
Number of clusters (mesa_code_elecspecific) =     76,130Root MSE  =     9.4302

                  (Std. err. adjusted for 76,130 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.92846   .0686972  -188.19   0.000     -13.0631   -12.
> 79381
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.027174   .0779292   -13.18   0.000    -1.179914   -.87
> 44326
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4537043   .9129521     0.50   0.619    -1.335677    2.2
> 43086
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -1.140525   1.718505    -0.66   0.507    -4.508786    2.2
> 27737
                   |
             _cons |   34.61844   .0115187  3005.42   0.000     34.59587    34.
> 64102
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76130       76130           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_4

. 
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (turnout_above_median_
> p3 == 1 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) clust
> er(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,902
Absorbing 1 HDFE group                            F(   5,  76129) =   52277.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9147
                                                  Adj R-squared   =     0.8643
                                                  Within R-sq.    =     0.7266
Number of clusters (mesa_code_elecspecific) =     76,130Root MSE  =     6.4927

                  (Std. err. adjusted for 76,130 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.32767   .0738545  -275.24   0.000    -20.47242   -20.
> 18291
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2105625   .0751799     2.80   0.005     .0632103    .35
> 79147
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7514515   .7391676     1.02   0.309    -.6973134    2.2
> 00216
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -5.005515   .9160036    -5.46   0.000    -6.800878   -3.2
> 10152
                   |
            period |
                2  |  -14.03912   .0365262  -384.36   0.000    -14.11071   -13.
> 96753
                3  |          0  (omitted)
                   |
             _cons |   41.22982   .0235982  1747.16   0.000     41.18356    41.
> 27607
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76130       76130           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_5

. 
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (turnout_above_median_
> p3 == 0 | turnout_above_median_p3 == 2), absorb(mesa_code_elecspecific) clust
> er(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,902
Absorbing 1 HDFE group                            F(   5,  76129) =   52080.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9147
                                                  Adj R-squared   =     0.8643
                                                  Within R-sq.    =     0.7266
Number of clusters (mesa_code_elecspecific) =     76,130Root MSE  =     6.4929

                  (Std. err. adjusted for 76,130 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.32833   .0738546  -275.25   0.000    -20.47309   -20.
> 18358
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2106738   .0751799     2.80   0.005     .0633216     .3
> 58026
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .8333907   .9128248     0.91   0.361    -.9557416    2.6
> 22523
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.378372   1.718391    -1.38   0.166     -5.74641    .98
> 96658
                   |
            period |
                2  |  -14.04038   .0365271  -384.38   0.000    -14.11197   -13.
> 96879
                3  |          0  (omitted)
                   |
             _cons |   41.22922   .0235988  1747.09   0.000     41.18297    41.
> 27547
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76130       76130           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_hte_turnout_6

. 
. * Make table
. esttab twoperiods_hte_turnout_1 twoperiods_hte_turnout_2 twoperiods_hte_turno
> ut_3 twoperiods_hte_turnout_4 twoperiods_hte_turnout_5 twoperiods_hte_turnout
> _6 using 03_tables/tabled1.tex, tex se replace mtitles ("Turnout above median
> " "Turnout below median" "Turnout above median" "Turnout below median" "Turno
> ut above median" "Turnout below median")  keep (1.post 1.post#1.ep 1.post#1.c
> iutadella 1.post#1.ep#1.ciutadella 2.period) coeflabels (1.post "2019 electio
> n" 2.period "2014-2015 election" d1.post#1.ep "EP election in 2019" 1.post#1.
> ciutadella "Ciutadella in 2019" 1.post#1.ep "EP election in 2019" 1.post#1.ep
> #1.ciutadella "EP 2019 x Ciutadella" "2014-2015 election") star(* 0.10 ** 0.0
> 5 *** 0.01) addnotes("All models include voting station * election type fixed
>  effects" "Standard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled1.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled2.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA < 18, absor
> b(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 32013 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    117,934
Absorbing 1 HDFE group                            F(   4,  58966) =   10521.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4036
Number of clusters (mesa_code_elecspecific) =     58,967Root MSE  =     5.2178

                  (Std. err. adjusted for 58,967 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.083933    .063095   -96.42   0.000      -6.2076   -5.9
> 60267
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0207659    .071462     0.29   0.771    -.1193001    .16
> 08318
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    1.13002   .6933797     1.63   0.103    -.2290071    2.4
> 89047
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.126266   1.121951    -2.79   0.005    -5.325296   -.92
> 72369
                   |
             _cons |   27.36519   .0151938  1801.08   0.000     27.33541    27.
> 39497
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     58967       58967           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_pp_ddd_excl

. 
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA < 18, absorb(mesa_code_e
> lecspecific) cluster(mesa_code_elecspecific)
(dropped 26189 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,069
Absorbing 1 HDFE group                            F(   4,  75814) =   44847.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8197
                                                  Adj R-squared   =     0.7131
                                                  Within R-sq.    =     0.4227
Number of clusters (mesa_code_elecspecific) =     75,815Root MSE  =     9.4245

                  (Std. err. adjusted for 75,815 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   -12.8905   .0689574  -186.93   0.000    -13.02566   -12.
> 75534
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.042796   .0781473   -13.34   0.000    -1.195964   -.88
> 96278
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    .374794   .5894712     0.64   0.525    -.7805667    1.5
> 30155
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.438529   1.008388    -2.42   0.016    -4.414964   -.46
> 20944
                   |
             _cons |   34.54986   .0115196  2999.22   0.000     34.52728    34.
> 57244
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75815       75815           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_pp_ddd_excl

. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA < 18, absorb(me
> sa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 26189 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,069
Absorbing 1 HDFE group                            F(   5,  75814) =   51952.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9146
                                                  Adj R-squared   =     0.8641
                                                  Within R-sq.    =     0.7265
Number of clusters (mesa_code_elecspecific) =     75,815Root MSE  =     6.4869

                  (Std. err. adjusted for 75,815 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.28726   .0741108  -273.74   0.000    -20.43251     -2
> 0.142
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1933874   .0753874     2.57   0.010     .0456285    .34
> 11463
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7536715   .5892698     1.28   0.201    -.4012946    1.9
> 08638
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.674713   1.008184    -3.64   0.000    -5.650749   -1.6
> 98676
                   |
            period |
                2  |  -14.03575   .0366123  -383.36   0.000    -14.10751     -1
> 3.964
                3  |          0  (omitted)
                   |
             _cons |   41.15768    .023637  1741.24   0.000     41.11135    41.
> 20401
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75815       75815           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_pp_ddd_excl

. 
. * Make table
. esttab twoperiods_pp_ddd_excl prepost_pp_ddd_excl threeperiods_pp_ddd_excl us
> ing 03_tables/tabled2.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2
> 009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutad
> ella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in
>  2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 
> 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.0
> 1) addnotes("All models include voting station * election type fixed effects"
>  "Standard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled2.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled3.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_not
> elecspecific) cluster(mesa_code_notelecspecific)
(dropped 19422 singleton observations)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    131,212
Absorbing 1 HDFE group                            F(   6,  50410) =    6496.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9115
                                                  Adj R-squared   =     0.8562
                                                  Within R-sq.    =     0.3122
Number of clusters (mesa_code_notelecspecific) =     50,411Root MSE=     5.5233

               (Std. err. adjusted for 50,411 clusters in mesa_code_notelecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -5.961871   .0621343   -95.95   0.000    -6.083655   -5.8
> 40088
              1.ep |   .0679477   .0632157     1.07   0.282    -.0559557    .19
> 18512
                   |
           post#ep |
              1 1  |  -.1204319   .0666023    -1.81   0.071    -.2509731    .01
> 01093
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.007958   .6932979     1.45   0.146    -.3509135     2.
> 36683
                   |
     ep#ciutadella |
              1 1  |    1.13959   .6664011     1.71   0.087    -.1665638    2.4
> 45743
                   |
post#ep#ciutadella |
            1 1 1  |  -2.985068   .7370404    -4.05   0.000    -4.429676   -1.5
> 40461
                   |
             _cons |   27.19558   .0476963   570.18   0.000      27.1021    27.
> 28907
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
-------------------------------------------------------------------+
               Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------------------+---------------------------------------|
 mesa_code_notelecspecific |     50411       50411           0    *|
-------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_ddd_cluster

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_notelecspecific) 
> cluster(mesa_code_notelecspecific)
(dropped 16098 singleton observations)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    215,191
Absorbing 1 HDFE group                            F(   6,  62043) =   26171.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8083
                                                  Adj R-squared   =     0.7307
                                                  Within R-sq.    =     0.3932
Number of clusters (mesa_code_notelecspecific) =     62,044Root MSE=     9.1796

               (Std. err. adjusted for 62,044 clusters in mesa_code_notelecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.76107    .067508  -189.03   0.000    -12.89338   -12.
> 62875
              1.ep |   1.696387   .0563313    30.11   0.000     1.585978    1.8
> 06797
                   |
           post#ep |
              1 1  |  -1.106767   .0679963   -16.28   0.000     -1.24004   -.97
> 34937
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .2453592   .5893067     0.42   0.677    -.9096832    1.4
> 00402
                   |
     ep#ciutadella |
              1 1  |  -.1130251   .7162968    -0.16   0.875    -1.516968    1.2
> 90918
                   |
post#ep#ciutadella |
            1 1 1  |  -2.374559   .7799553    -3.04   0.002    -3.903273   -.84
> 58446
                   |
             _cons |   33.48393   .0426622   784.86   0.000     33.40031    33.
> 56755
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
-------------------------------------------------------------------+
               Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------------------+---------------------------------------|
 mesa_code_notelecspecific |     62044       62044           0    *|
-------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_ddd_cluster

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_notelecs
> pecific) cluster(mesa_code_notelecspecific)
(dropped 16098 singleton observations)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    215,191
Absorbing 1 HDFE group                            F(   7,  62043) =   31857.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8997
                                                  Adj R-squared   =     0.8591
                                                  Within R-sq.    =     0.6826
Number of clusters (mesa_code_notelecspecific) =     62,044Root MSE=     6.6396

               (Std. err. adjusted for 62,044 clusters in mesa_code_notelecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.08696   .0745255  -269.53   0.000    -20.23303   -19.
> 94089
              1.ep |   .6974151   .0538649    12.95   0.000     .5918398    .80
> 29905
                   |
           post#ep |
              1 1  |  -.0808449   .0665346    -1.22   0.224    -.2112529    .04
> 95632
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .5363122    .589119     0.91   0.363    -.6183623    1.6
> 90987
                   |
     ep#ciutadella |
              1 1  |   .8859473   .7160947     1.24   0.216    -.5175999    2.2
> 89494
                   |
post#ep#ciutadella |
            1 1 1  |   -3.40048   .7798207    -4.36   0.000    -4.928931    -1.
> 87203
                   |
            period |
                2  |  -14.06989   .0392235  -358.71   0.000    -14.14677   -13.
> 99301
                3  |          0  (omitted)
                   |
             _cons |   40.71148   .0489205   832.20   0.000     40.61559    40.
> 80736
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
-------------------------------------------------------------------+
               Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------------------+---------------------------------------|
 mesa_code_notelecspecific |     62044       62044           0    *|
-------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_ddd_cluster

. 
. * Make table
. esttab twoperiods_ddd_cluster prepost_ddd_cluster threeperiods_ddd_cluster us
> ing 03_tables/tabled3.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2
> 009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutad
> ella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in
>  2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 
> 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.0
> 1) addnotes("All models include voting station fixed effects" "Standard error
> s are clustered by voting station") 
(output written to 03_tables/tabled3.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled4.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain_2.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_ele
> cspecific) cluster(mesa_code_elecspecific)
(dropped 32172 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,470
Absorbing 1 HDFE group                            F(   4,  59234) =   10592.53
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4046
Number of clusters (mesa_code_elecspecific) =     59,235Root MSE  =     5.2282

                  (Std. err. adjusted for 59,235 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.121899    .062844   -97.41   0.000    -6.245074   -5.9
> 98725
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0404565   .0712617     0.57   0.570    -.0992168    .18
> 01298
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.248487   .6684944     1.87   0.062     -.061765    2.5
> 58739
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.891406   1.168785    -2.47   0.013    -5.182229   -.60
> 05829
                   |
             _cons |   27.43679   .0151896  1806.28   0.000     27.40702    27.
> 46656
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59235       59235           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_tables

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) clu
> ster(mesa_code_elecspecific)
(dropped 26311 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,988
Absorbing 1 HDFE group                            F(   4,  76160) =   45015.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8200
                                                  Adj R-squared   =     0.7136
                                                  Within R-sq.    =     0.4234
Number of clusters (mesa_code_elecspecific) =     76,161Root MSE  =     9.4294

                  (Std. err. adjusted for 76,161 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.92846   .0686972  -188.19   0.000     -13.0631   -12.
> 79381
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.027174   .0779292   -13.18   0.000    -1.179914   -.87
> 44326
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .9956336   .5962998     1.67   0.095     -.173111    2.1
> 64378
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -3.06124   1.032842    -2.96   0.003    -5.085605   -1.0
> 36875
                   |
             _cons |   34.61929   .0115141  3006.69   0.000     34.59673    34.
> 64186
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76161       76161           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_tables

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspec
> ific) cluster(mesa_code_elecspecific)
(dropped 26311 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,988
Absorbing 1 HDFE group                            F(   5,  76160) =   52218.62
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9147
                                                  Adj R-squared   =     0.8643
                                                  Within R-sq.    =     0.7267
Number of clusters (mesa_code_elecspecific) =     76,161Root MSE  =     6.4917

                  (Std. err. adjusted for 76,161 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.32833   .0738505  -275.26   0.000    -20.47308   -20.
> 18359
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2106738   .0751797     2.80   0.005      .063322    .35
> 80256
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.005836   .5346946     1.88   0.060    -.0421625    2.0
> 53835
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.532234   .9926123    -3.56   0.000    -5.477749   -1.5
> 86719
                   |
            period |
                2  |  -14.04038   .0365116  -384.55   0.000    -14.11194   -13.
> 96882
                3  |          0  (omitted)
                   |
             _cons |   41.23024    .023589  1747.86   0.000     41.18401    41.
> 27648
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76161       76161           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_tables

. 
. * Make table
. esttab twoperiods_tables prepost_tables threeperiods_tables using 03_tables/t
> abled4.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019")  kee
> p (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutadella 2.period) 
> coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019" 1.post#1
> .ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 2019 x Ciutadel
> la" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) addnotes("Al
> l models include voting station * election type fixed effects" "Standard erro
> rs are clustered by voting station * election type") 
(output written to 03_tables/tabled4.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled5.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & menorca_not_ciutade
> lla == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 32155 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,266
Absorbing 1 HDFE group                            F(   4,  59132) =   10633.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8748
                                                  Within R-sq.    =     0.4056
Number of clusters (mesa_code_elecspecific) =     59,133Root MSE  =     5.2258

                  (Std. err. adjusted for 59,133 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.130789   .0630196   -97.28   0.000    -6.254307    -6.
> 00727
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0384034   .0714038     0.54   0.591    -.1015485    .17
> 83552
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.176875   .6933728     1.70   0.090    -.1821382    2.5
> 35889
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.143904   1.121948    -2.80   0.005    -5.342926    -.9
> 44882
                   |
             _cons |   27.42166   .0151956  1804.58   0.000     27.39187    27.
> 45144
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59133       59133           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_menorca_notciuta

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if menorca_not_ciutadella == 0, abs
> orb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 26289 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,697
Absorbing 1 HDFE group                            F(   4,  76052) =   45120.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8201
                                                  Adj R-squared   =     0.7138
                                                  Within R-sq.    =     0.4239
Number of clusters (mesa_code_elecspecific) =     76,053Root MSE  =     9.4298

                  (Std. err. adjusted for 76,053 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.95539   .0688113  -188.27   0.000    -13.09026   -12.
> 82052
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.010137    .078023   -12.95   0.000    -1.163062   -.85
> 72125
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4396813   .5894541     0.75   0.456    -.7156459    1.5
> 95008
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.471188   1.008378    -2.45   0.014    -4.447604   -.49
> 47723
                   |
             _cons |   34.61236    .011515  3005.84   0.000     34.58979    34.
> 63493
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76053       76053           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_menorca_notciuta

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period if menorca_not_ciutadella 
> == 0, absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 26289 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,697
Absorbing 1 HDFE group                            F(   5,  76052) =   52274.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9148
                                                  Adj R-squared   =     0.8645
                                                  Within R-sq.    =     0.7272
Number of clusters (mesa_code_elecspecific) =     76,053Root MSE  =     6.4885

                  (Std. err. adjusted for 76,053 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.35582   .0739228  -275.37   0.000    -20.50071   -20.
> 21094
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2266209   .0752643     3.01   0.003     .0791032    .37
> 41385
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .8163838   .5892535     1.39   0.166    -.3385503    1.9
> 71318
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.707946   1.008175    -3.68   0.000    -5.683965   -1.7
> 31928
                   |
            period |
                2  |  -14.04747   .0365178  -384.67   0.000    -14.11904   -13.
> 97589
                3  |          0  (omitted)
                   |
             _cons |   41.22459   .0235857  1747.86   0.000     41.17836    41.
> 27081
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76053       76053           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeper_menorca_notciuta

. 
. * Make table
. esttab twoperiods_menorca_notciuta prepost_menorca_notciuta threeper_menorca_
> notciuta using 03_tables/tabled5.tex, tex se replace mtitles ("2014-2019" "20
> 09-2019" "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.
> ep#1.ciutadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP 
> election in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciut
> adella "EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0
> .05 *** 0.01) addnotes("All models include voting station * election type fix
> ed effects" "Standard errors are clustered by voting station * election type"
> ) 
(output written to 03_tables/tabled5.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled6.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_ele
> cspecific) cluster(mesa_code_elecspecific)
(dropped 116 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =      4,988
Absorbing 1 HDFE group                            F(   4,   2493) =     523.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8471
                                                  Adj R-squared   =     0.6938
                                                  Within R-sq.    =     0.2334
Number of clusters (mesa_code_elecspecific) =      2,494Root MSE  =     6.1161

                   (Std. err. adjusted for 2,494 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   3.311371   .2367953    13.98   0.000     2.847036    3.7
> 75707
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   3.863518   .2980471    12.96   0.000     3.279072    4.4
> 47963
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   -9.44922   .4591344   -20.58   0.000    -10.34954   -8.5
> 48896
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -5.785083   1.010611    -5.72   0.000    -7.766805    -3.
> 80336
                   |
             _cons |   26.87835   .0865808   310.44   0.000     26.70857    27.
> 04812
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2494        2494           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_ddd_balearic

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) clu
> ster(mesa_code_elecspecific)
(dropped 186 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =      7,331
Absorbing 1 HDFE group                            F(   4,   2518) =     605.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4601
                                                  Adj R-squared   =     0.1770
                                                  Within R-sq.    =     0.0656
Number of clusters (mesa_code_elecspecific) =      2,519Root MSE  =    11.6662

                   (Std. err. adjusted for 2,519 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -5.060086   .2447877   -20.67   0.000    -5.540091    -4.
> 58008
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   4.483275   .3021298    14.84   0.000     3.890827    5.0
> 75723
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -9.347174   .4354706   -21.46   0.000    -10.20109   -8.4
> 93257
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -6.073047   .9431975    -6.44   0.000    -7.922569   -4.2
> 23525
                   |
             _cons |    35.2196   .0610412   576.98   0.000     35.09991     35
> .3393
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2519        2519           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_ddd_balearic

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecspec
> ific) cluster(mesa_code_elecspecific)
(dropped 186 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =      7,331
Absorbing 1 HDFE group                            F(   5,   2518) =    1360.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7555
                                                  Adj R-squared   =     0.6272
                                                  Within R-sq.    =     0.5768
Number of clusters (mesa_code_elecspecific) =      2,519Root MSE  =     7.8518

                   (Std. err. adjusted for 2,519 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -14.28716   .3173385   -45.02   0.000    -14.90943   -13.
> 66489
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   4.432166   .2929286    15.13   0.000     3.857761    5.0
> 06572
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -8.838635   .4364059   -20.25   0.000    -9.694386   -7.9
> 82884
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -6.021938   .9403472    -6.40   0.000    -7.865871   -4.1
> 78005
                   |
            period |
                2  |  -17.43707   .2511476   -69.43   0.000    -17.92955    -16
> .9446
                3  |          0  (omitted)
                   |
             _cons |   44.33115   .1632511   271.55   0.000     44.01103    44.
> 65127
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2519        2519           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_ddd_balearic

. 
. * Make table
. esttab twoperiods_ddd_balearic prepost_ddd_balearic threeperiods_ddd_balearic
>  using 03_tables/tabled6.tex, tex se replace mtitles ("2014-2019" "2009-2019"
>  "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciu
> tadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election
>  in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "
> EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 
> 0.01) addnotes("All models include voting station * election type fixed effec
> ts" "Standard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled6.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled7.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & menorca == 1 , abso
> rb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 6 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =        504
Absorbing 1 HDFE group                            F(   4,    251) =     111.49
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9333
                                                  Adj R-squared   =     0.8647
                                                  Within R-sq.    =     0.5873
Number of clusters (mesa_code_elecspecific) =        252Root MSE  =     3.2610

                     (Std. err. adjusted for 252 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -3.131429   .5229786    -5.99   0.000    -4.161414   -2.1
> 01443
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |       9.66   .8749137    11.04   0.000     7.936892    11.
> 38311
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   -3.00642   .6556771    -4.59   0.000     -4.29775    -1.
> 71509
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -11.58156   1.306928    -8.86   0.000    -14.15551   -9.0
> 07622
                   |
             _cons |    32.1203    .144964   221.57   0.000      31.8348     32
> .4058
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |       252         252           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_ddd_menorca

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if menorca == 1, absorb(mesa_code_e
> lecspecific) cluster(mesa_code_elecspecific)
(dropped 16 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =        730
Absorbing 1 HDFE group                            F(   4,    252) =     523.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6298
                                                  Adj R-squared   =     0.4294
                                                  Within R-sq.    =     0.3959
Number of clusters (mesa_code_elecspecific) =        253Root MSE  =     7.8509

                     (Std. err. adjusted for 253 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.358728   .5646694   -11.26   0.000    -7.470801   -5.2
> 46656
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   6.730818   1.033938     6.51   0.000     4.694556    8.7
> 67079
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -8.048532   .6705781   -12.00   0.000    -9.369183    -6.
> 72788
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -8.32059   1.369014    -6.08   0.000    -11.01676   -5.6
> 24424
                   |
             _cons |   38.06409   .1055714   360.55   0.000     37.85618    38.
> 27201
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |       253         253           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_ddd_menorca

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period if menorca == 1 , absorb(m
> esa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 16 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =        730
Absorbing 1 HDFE group                            F(   5,    252) =     512.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8690
                                                  Adj R-squared   =     0.7977
                                                  Within R-sq.    =     0.7863
Number of clusters (mesa_code_elecspecific) =        253Root MSE  =     4.6741

                     (Std. err. adjusted for 253 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.66513   .7634309   -17.90   0.000    -15.16865   -12.
> 16161
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   6.494382    .997023     6.51   0.000     4.530823    8.4
> 57942
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   -7.13922   .7131768   -10.01   0.000    -8.543766   -5.7
> 34674
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -8.084154   1.341706    -6.03   0.000    -10.72654   -5.4
> 41768
                   |
            period |
                2  |  -12.79418   .5084243   -25.16   0.000    -13.79548   -11.
> 79288
                3  |          0  (omitted)
                   |
             _cons |   44.88508   .3262764   137.57   0.000      44.2425    45.
> 52766
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |       253         253           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_ddd_menorca

. 
. * Make table
. esttab twoperiods_ddd_menorca prepost_ddd_menorca threeperiods_ddd_menorca us
> ing 03_tables/tabled7.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2
> 009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciutad
> ella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in
>  2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "EP 
> 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.0
> 1) addnotes("All models include voting station * election type fixed effects"
>  "Standard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled7.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled8.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/balearic_plus_ciutadella.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & (ciutadella == 1 | 
> mallorca == 1), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific
> )
(dropped 95 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =      4,098
Absorbing 1 HDFE group                            F(   4,   2048) =     448.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8200
                                                  Adj R-squared   =     0.6393
                                                  Within R-sq.    =     0.2548
Number of clusters (mesa_code_elecspecific) =      2,049Root MSE  =     6.2328

                   (Std. err. adjusted for 2,049 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   3.973507   .2698277    14.73   0.000     3.444342    4.5
> 02673
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   3.228877   .3381498     9.55   0.000     2.565724    3.8
> 92031
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -10.11136   .4770533   -21.20   0.000    -11.04692   -9.1
> 75796
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -5.150442   1.023275    -5.03   0.000    -7.157209   -3.1
> 43674
                   |
             _cons |   25.20978   .0973405   258.99   0.000     25.01889    25.
> 40068
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2049        2049           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_ddd_mallorca

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##ciutadella if (ciutadella == 1 | mallorca == 1
> ), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 153 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =      6,053
Absorbing 1 HDFE group                            F(   4,   2071) =     579.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3803
                                                  Adj R-squared   =     0.0570
                                                  Within R-sq.    =     0.0644
Number of clusters (mesa_code_elecspecific) =      2,072Root MSE  =    12.2646

                   (Std. err. adjusted for 2,072 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -5.130331   .2879499   -17.82   0.000    -5.695032   -4.5
> 65629
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   4.367989   .3444613    12.68   0.000     3.692463    5.0
> 43516
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -9.276929   .4611452   -20.12   0.000    -10.18129   -8.3
> 72573
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -5.957761   .9576812    -6.22   0.000    -7.835879   -4.0
> 79643
                   |
             _cons |   34.12445   .0702193   485.97   0.000     33.98674    34.
> 26215
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2072        2072           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_ddd_mallorca

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##ciutadella i.period  if (ciutadella == 1 | mal
> lorca == 1), absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 153 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =      6,053
Absorbing 1 HDFE group                            F(   5,   2071) =    1237.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7243
                                                  Adj R-squared   =     0.5803
                                                  Within R-sq.    =     0.5836
Number of clusters (mesa_code_elecspecific) =      2,072Root MSE  =     8.1825

                   (Std. err. adjusted for 2,072 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -14.82275   .3727411   -39.77   0.000    -15.55373   -14.
> 09176
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   4.442523   .3373113    13.17   0.000     3.781018    5.1
> 04027
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -8.797905   .4617805   -19.05   0.000    -9.703508   -7.8
> 92303
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -6.032295    .955204    -6.32   0.000    -7.905555   -4.1
> 59034
                   |
            period |
                2  |  -18.42678   .2859877   -64.43   0.000    -18.98764   -17.
> 86593
                3  |          0  (omitted)
                   |
             _cons |   43.67906   .1871117   233.44   0.000     43.31212    44.
> 04601
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |      2072        2072           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_ddd_mallorca

. 
. * Make table
. esttab twoperiods_ddd_mallorca prepost_ddd_mallorca threeperiods_ddd_mallorca
>  using 03_tables/tabled8.tex, tex se replace mtitles ("2014-2019" "2009-2019"
>  "2009-2019")  keep (1.post 1.post#1.ep 1.post#1.ciutadella 1.post#1.ep#1.ciu
> tadella 2.period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election
>  in 2019" 1.post#1.ciutadella "Ciutadella in 2019" 1.post#1.ep#1.ciutadella "
> EP 2019 x Ciutadella" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 
> 0.01) addnotes("All models include voting station * election type fixed effec
> ts" "Standard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled8.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled9.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. use 01_data/whole_spain.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep##menorca if period > 1 & ciutadella == 0, absor
> b(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 32160 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.menorca is probably collinear with the fixed effects (all partialled-
> out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.menorca is probably collinear with the fixed effects (all part
> ialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.menorca omitted because of collinearity
note: 1.ep#1.menorca omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,362
Absorbing 1 HDFE group                            F(   4,  59180) =   10629.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9375
                                                  Adj R-squared   =     0.8750
                                                  Within R-sq.    =     0.4055
Number of clusters (mesa_code_elecspecific) =     59,181Root MSE  =     5.2250

               (Std. err. adjusted for 59,181 clusters in mesa_code_elecspecifi
> c)
-------------------------------------------------------------------------------
--
                |               Robust
   pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interva
> l]
----------------+--------------------------------------------------------------
--
         1.post |  -6.130789   .0630196   -97.28   0.000    -6.254307    -6.007
> 27
           1.ep |          0  (omitted)
                |
        post#ep |
           1 1  |   .0384034   .0714038     0.54   0.591    -.1015484    .17835
> 52
                |
      1.menorca |          0  (omitted)
                |
   post#menorca |
           1 1  |   2.423542   .6617132     3.66   0.000     1.126582    3.7205
> 03
                |
     ep#menorca |
           1 1  |          0  (omitted)
                |
post#ep#menorca |
         1 1 1  |   10.19741   .9618391    10.60   0.000     8.312206    12.082
> 62
                |
          _cons |   27.43683   .0151872  1806.57   0.000     27.40707     27.46
> 66
-------------------------------------------------------------------------------
--

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59181       59181           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods_ddd_menplcb

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep##menorca if ciutadella == 0, absorb(mesa_code_e
> lecspecific) cluster(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.menorca is probably collinear with the fixed effects (all partialled-
> out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.menorca is probably collinear with the fixed effects (all part
> ialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.menorca omitted because of collinearity
note: 1.ep#1.menorca omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,818
Absorbing 1 HDFE group                            F(   4,  76101) =   44923.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8202
                                                  Adj R-squared   =     0.7139
                                                  Within R-sq.    =     0.4237
Number of clusters (mesa_code_elecspecific) =     76,102Root MSE  =     9.4274

               (Std. err. adjusted for 76,102 clusters in mesa_code_elecspecifi
> c)
-------------------------------------------------------------------------------
--
                |               Robust
   pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interva
> l]
----------------+--------------------------------------------------------------
--
         1.post |  -12.95539   .0688113  -188.27   0.000    -13.09026   -12.820
> 52
           1.ep |          0  (omitted)
                |
        post#ep |
           1 1  |  -1.010137    .078023   -12.95   0.000    -1.163062   -.85721
> 25
                |
      1.menorca |          0  (omitted)
                |
   post#menorca |
           1 1  |   7.801888   .7084319    11.01   0.000     6.413365    9.1904
> 11
                |
     ep#menorca |
           1 1  |          0  (omitted)
                |
post#ep#menorca |
         1 1 1  |   6.535727   1.116407     5.85   0.000     4.347574    8.7238
> 79
                |
          _cons |   34.61868   .0115109  3007.48   0.000     34.59612    34.641
> 24
-------------------------------------------------------------------------------
--

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76102       76102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_ddd_menplcb

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep##menorca i.period  if ciutadella == 0, absorb(m
> esa_code_elecspecific) cluster(mesa_code_elecspecific)
(dropped 26303 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.menorca is probably collinear with the fixed effects (all partialled-
> out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.menorca is probably collinear with the fixed effects (all part
> ialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.menorca omitted because of collinearity
note: 1.ep#1.menorca omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,818
Absorbing 1 HDFE group                            F(   5,  76101) =   52069.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9148
                                                  Adj R-squared   =     0.8644
                                                  Within R-sq.    =     0.7268
Number of clusters (mesa_code_elecspecific) =     76,102Root MSE  =     6.4907

               (Std. err. adjusted for 76,102 clusters in mesa_code_elecspecifi
> c)
-------------------------------------------------------------------------------
--
                |               Robust
   pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interva
> l]
----------------+--------------------------------------------------------------
--
         1.post |  -20.35036    .073924  -275.29   0.000    -20.49525   -20.205
> 47
           1.ep |          0  (omitted)
                |
        post#ep |
           1 1  |   .2257077   .0752646     3.00   0.003     .0781895     .3732
> 26
                |
      1.menorca |          0  (omitted)
                |
   post#menorca |
           1 1  |    6.88258   .7932997     8.68   0.000     5.327717    8.4374
> 44
                |
     ep#menorca |
           1 1  |          0  (omitted)
                |
post#ep#menorca |
         1 1 1  |    5.33856    1.12692     4.74   0.000     3.129803    7.5473
> 18
                |
         period |
             2  |   -14.0371    .036539  -384.17   0.000    -14.10871   -13.965
> 48
             3  |          0  (omitted)
                |
          _cons |   41.22774   .0235967  1747.18   0.000     41.18149    41.273
> 99
-------------------------------------------------------------------------------
--

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76102       76102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_ddd_menplcb

. 
. * Make table
. esttab twoperiods_ddd_menplcb prepost_ddd_menplcb threeperiods_ddd_menplcb us
> ing 03_tables/tabled9.tex, tex se replace mtitles ("2014-2019" "2009-2019" "2
> 009-2019")  keep (1.post 1.post#1.ep 1.post#1.menorca 1.post#1.ep#1.menorca 2
> .period) coeflabels (1.post "2019 election" 1.post#1.ep "EP election in 2019"
>  1.post#1.menorca "Menorca (outside of Ciutadella) in 2019" 1.post#1.ep#1.men
> orca "EP 2019 x Menorca" 2.period "2014-2015 election" post#ep#menorca "EP 20
> 19 x Menorca" 2.period "2014-2015 election") star(* 0.10 ** 0.05 *** 0.01) ad
> dnotes("All models include voting station * election type fixed effects" "Sta
> ndard errors are clustered by voting station * election type") 
(output written to 03_tables/tabled9.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled10.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/elections_ciutadella.dta, clear

. 
. * No fixed effects
. regr pp_voteshare ep if year == 2019, cluster(table_code_notelectionspecific)

Linear regression                               Number of obs     =        112
                                                F(1, 27)          =      74.19
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0636
                                                Root MSE          =     2.8336

        (Std. err. adjusted for 28 clusters in table_code_notelectionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ep |  -1.690054   .1962152    -8.61   0.000    -2.092655   -1.287454
       _cons |   21.91003   .5264531    41.62   0.000     20.82984    22.99022
------------------------------------------------------------------------------

. est store cross_section1

. estadd local  FE "No"

added macro:
                 e(FE) : "No"

. 
. * With voting station fixed effects
. regr pp_voteshare ep i.table_code_notelectionspecific if year == 2019, cluste
> r(table_code_notelectionspecific)

Linear regression                               Number of obs     =        112
                                                F(0, 27)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9213
                                                Root MSE          =      .9458

                          (Std. err. adjusted for 28 clusters in table_code_not
> electionspecific)
-------------------------------------------------------------------------------
-----------------
                               |               Robust
                  pp_voteshare | Coefficient  std. err.      t    P>|t|     [95
> % con                                                                        
>      f. interval]
-------------------------------+-----------------------------------------------
-----------------
                            ep |  -1.690054   .2258863    -7.48   0.000    -2.1
> 53535                                                                        
>         -1.226574
                               |
table_code_notelectionspecific |
                   0701501002  |  -4.197183          .        .       .        
>     .                                                                        
>                 .
                  0701501003A  |  -5.494924          .        .       .        
>     .                                                                        
>                 .
                  0701501003B  |  -1.105717          .        .       .        
>     .                                                                        
>                 .
                  0701501004A  |  -7.641188          .        .       .        
>     .                                                                        
>                 .
                  0701501004B  |  -7.826384          .        .       .        
>     .                                                                        
>                 .
                  0701501005A  |  -.2454538          .        .       .        
>     .                                                                        
>                 .
                  0701501005B  |    -.89465          .        .       .        
>     .                                                                        
>                 .
                  0701502001U  |   .0257592          .        .       .        
>     .                                                                        
>                 .
                  0701502002A  |  -4.208354          .        .       .        
>     .                                                                        
>                 .
                  0701502002B  |  -2.544674          .        .       .        
>     .                                                                        
>                 .
                  0701502003A  |  -4.038512          .        .       .        
>     .                                                                        
>                 .
                  0701502003B  |  -2.515619          .        .       .        
>     .                                                                        
>                 .
                   0701502004  |  -2.004235          .        .       .        
>     .                                                                        
>                 .
                  0701503001A  |  -1.152445          .        .       .        
>     .                                                                        
>                 .
                  0701503001B  |   3.056869          .        .       .        
>     .                                                                        
>                 .
                  0701503002A  |  -2.554738          .        .       .        
>     .                                                                        
>                 .
                  0701503002B  |    -.35847          .        .       .        
>     .                                                                        
>                 .
                  0701503003A  |  -3.088308          .        .       .        
>     .                                                                        
>                 .
                  0701503003B  |  -.3049059          .        .       .        
>     .                                                                        
>                 .
                  0701504001A  |   1.120821          .        .       .        
>     .                                                                        
>                 .
                  0701504001B  |   3.603041          .        .       .        
>     .                                                                        
>                 .
                  0701504002A  |  -2.944407          .        .       .        
>     .                                                                        
>                 .
                  0701504002B  |   .3941302          .        .       .        
>     .                                                                        
>                 .
                  0701504003A  |  -4.593906          .        .       .        
>     .                                                                        
>                 .
                  0701504003B  |  -.4619741          .        .       .        
>     .                                                                        
>                 .
                  0701504004A  |   .4198308          .        .       .        
>     .                                                                        
>                 .
                  0701504004B  |  -2.997019          .        .       .        
>     .                                                                        
>                 .
                               |
                         _cons |   23.78691   .0564716   421.22   0.000     23.
> 67104                                                                        
>          23.90278
-------------------------------------------------------------------------------
-----------------

. est store cross_section2

. estadd local  FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. * With dummies for each election type
. regr pp_voteshare ep municipal autonomic if year == 2019, cluster(table_code_
> notelectionspecific)

Linear regression                               Number of obs     =        112
                                                F(3, 27)          =      34.75
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0665
                                                Root MSE          =     2.8552

        (Std. err. adjusted for 28 clusters in table_code_notelectionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
          ep |  -1.717379   .2025925    -8.48   0.000    -2.133064   -1.301693
   municipal |   .1805841   .2956032     0.61   0.546    -.4259436    .7871118
   autonomic |  -.2625574   .2317561    -1.13   0.267    -.7380816    .2129668
       _cons |   21.93736   .5305449    41.35   0.000     20.84877    23.02594
------------------------------------------------------------------------------

. est store cross_section3

. estadd local  FE "No"

added macro:
                 e(FE) : "No"

. 
. * With dummies for each election type and voting station fixed effects
. regr pp_voteshare ep municipal autonomic i.table_code_notelectionspecific if 
> year == 2019, cluster(table_code_notelectionspecific)

Linear regression                               Number of obs     =        112
                                                F(2, 27)          =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9242
                                                Root MSE          =     .93931

                          (Std. err. adjusted for 28 clusters in table_code_not
> electionspecific)
-------------------------------------------------------------------------------
-----------------
                               |               Robust
                  pp_voteshare | Coefficient  std. err.      t    P>|t|     [95
> % con                                                                        
>      f. interval]
-------------------------------+-----------------------------------------------
-----------------
                            ep |  -1.717379   .2339336    -7.34   0.000    -2.1
> 97371                                                                        
>         -1.237387
                     municipal |   .1805841   .3413332     0.53   0.601    -.51
> 97738                                                                        
>           .880942
                     autonomic |  -.2625574   .2676089    -0.98   0.335    -.81
> 16455                                                                        
>          .2865307
                               |
table_code_notelectionspecific |
                   0701501002  |  -4.197183          .        .       .        
>     .                                                                        
>                 .
                  0701501003A  |  -5.494924          .        .       .        
>     .                                                                        
>                 .
                  0701501003B  |  -1.105717          .        .       .        
>     .                                                                        
>                 .
                  0701501004A  |  -7.641188          .        .       .        
>     .                                                                        
>                 .
                  0701501004B  |  -7.826384          .        .       .        
>     .                                                                        
>                 .
                  0701501005A  |  -.2454538          .        .       .        
>     .                                                                        
>                 .
                  0701501005B  |    -.89465          .        .       .        
>     .                                                                        
>                 .
                  0701502001U  |   .0257592          .        .       .        
>     .                                                                        
>                 .
                  0701502002A  |  -4.208354          .        .       .        
>     .                                                                        
>                 .
                  0701502002B  |  -2.544674          .        .       .        
>     .                                                                        
>                 .
                  0701502003A  |  -4.038512          .        .       .        
>     .                                                                        
>                 .
                  0701502003B  |  -2.515619          .        .       .        
>     .                                                                        
>                 .
                   0701502004  |  -2.004235          .        .       .        
>     .                                                                        
>                 .
                  0701503001A  |  -1.152445          .        .       .        
>     .                                                                        
>                 .
                  0701503001B  |   3.056869          .        .       .        
>     .                                                                        
>                 .
                  0701503002A  |  -2.554738          .        .       .        
>     .                                                                        
>                 .
                  0701503002B  |    -.35847          .        .       .        
>     .                                                                        
>                 .
                  0701503003A  |  -3.088308          .        .       .        
>     .                                                                        
>                 .
                  0701503003B  |  -.3049059          .        .       .        
>     .                                                                        
>                 .
                  0701504001A  |   1.120821          .        .       .        
>     .                                                                        
>                 .
                  0701504001B  |   3.603041          .        .       .        
>     .                                                                        
>                 .
                  0701504002A  |  -2.944407          .        .       .        
>     .                                                                        
>                 .
                  0701504002B  |   .3941302          .        .       .        
>     .                                                                        
>                 .
                  0701504003A  |  -4.593906          .        .       .        
>     .                                                                        
>                 .
                  0701504003B  |  -.4619741          .        .       .        
>     .                                                                        
>                 .
                  0701504004A  |   .4198308          .        .       .        
>     .                                                                        
>                 .
                  0701504004B  |  -2.997019          .        .       .        
>     .                                                                        
>                 .
                               |
                         _cons |   23.81423   .1683037   141.50   0.000      23
> .4689                                                                        
>          24.15957
-------------------------------------------------------------------------------
-----------------

. est store cross_section4

. estadd local  FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. * Make table
. esttab cross_section1 cross_section2 cross_section3 cross_section4 using 03_t
> ables/tabled10.tex, tex se replace nomtitles keep(ep municipal autonomic _con
> s) coeflabels (ep "European election" municipal "Municipal election" autonomi
> c "Autonomic election" _cons "Constant") s(FE, label("Voting station fixed ef
> fects")) star(* 0.10 ** 0.05 *** 0.01) addnotes("Standard errors are clustere
> d by voting station" "In models 3 and 4, the reference category are Elections
>  for the Balearic Council.") scalars(e(N))
(output written to 03_tables/tabled10.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled11.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/elections_ciutadella.dta, clear

. 
. * 2014/5-2019
. reghdfe pp_voteshare post##ep  if period > 1 , absorb(table_code_electionspec
> ific) cluster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity

HDFE Linear regression                            Number of obs   =        224
Absorbing 1 HDFE group                            F(   2,    111) =     160.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8424
                                                  Adj R-squared   =     0.6806
                                                  Within R-sq.    =     0.7457
Number of clusters (table_code_electionspecific) =        112Root MSE=     2.77
> 94

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -6.137849   .3966734   -15.47   0.000    -6.923884   -5.351814
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -1.921565   .9737946    -1.97   0.051    -3.851204    .0080743
             |
       _cons |   28.10576   .1857028   151.35   0.000     27.73778    28.47374
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store twoperiods

. 
. * Pre vs. post
. reghdfe pp_voteshare post##ep, absorb(table_code_electionspecific) cluster(ta
> ble_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity

HDFE Linear regression                            Number of obs   =        336
Absorbing 1 HDFE group                            F(   2,    111) =     977.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5439
                                                  Adj R-squared   =     0.3117
                                                  Within R-sq.    =     0.4957
Number of clusters (table_code_electionspecific) =        112Root MSE=     8.66
> 97

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -14.40726   .3626902   -39.72   0.000    -15.12595   -13.68857
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -1.589772   .8997809    -1.77   0.080    -3.372748    .1932039
             |
       _cons |   36.29222   .1137114   319.16   0.000     36.06689    36.51755
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period, absorb(table_code_electionspecific) c
> luster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =        336
Absorbing 1 HDFE group                            F(   3,    111) =    1337.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9542
                                                  Adj R-squared   =     0.9306
                                                  Within R-sq.    =     0.9494
Number of clusters (table_code_electionspecific) =        112Root MSE=     2.75
> 24

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -22.59372   .4078674   -55.39   0.000    -23.40194   -21.78551
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -1.589772    .901135    -1.76   0.080    -3.375431    .1958871
             |
      period |
          2  |  -16.37293   .3408076   -48.04   0.000    -17.04826   -15.69759
          3  |          0  (omitted)
             |
       _cons |   44.47868   .2110707   210.73   0.000     44.06043    44.89693
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods

. 
. * 2009/11-2014/5 (Placebo)
. reghdfe pp_voteshare_lag post##ep, absorb(table_code_electionspecific) cluste
> r(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity

HDFE Linear regression                            Number of obs   =        224
Absorbing 1 HDFE group                            F(   2,    111) =    1236.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9631
                                                  Adj R-squared   =     0.9252
                                                  Within R-sq.    =     0.9548
Number of clusters (table_code_electionspecific) =        112Root MSE=     0.02
> 54

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_votesha~g | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -.1653882   .0036099   -45.82   0.000    -.1725415    -.158235
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |   .0066359   .0089661     0.74   0.461     -.011131    .0244028
             |
       _cons |   .4447868   .0016985   261.87   0.000     .4414211    .4481526
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store placebo

. 
. * Make table
. esttab twoperiods prepost threeperiods placebo using 03_tables/tabled11.tex, 
> tex se replace mtitles ("2014-2019" "2009-2019" "2009-2019" "Placebo with lag
> ged outcome")  keep (1.post 1.post#1.ep 2.period) coeflabels (1.post#1.ep "Tr
> eatment (absence of booth)" 1.post "2019" 2.period "2014-5") star(* 0.10 ** 0
> .05 *** 0.01) addnotes("All models include voting station * election type fix
> ed effects" "Standard errors are clustered by voting station * election type"
> )
(output written to 03_tables/tabled11.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled12.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/elections_ciutadella_more_years, clear

. 
. * Grouping 2003 and 2004 together
. * Pre vs. post
. reghdfe pp_voteshare post##ep if period3 != ., absorb(table_code_electionspec
> ific) cluster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity

HDFE Linear regression                            Number of obs   =        420
Absorbing 1 HDFE group                            F(   2,    111) =    1412.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5651
                                                  Adj R-squared   =     0.4044
                                                  Within R-sq.    =     0.5151
Number of clusters (table_code_electionspecific) =        112Root MSE=     8.69
> 68

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -15.91934   .3465982   -45.93   0.000    -16.60614   -15.23253
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -5.028055   .8559697    -5.87   0.000    -6.724216   -3.331894
             |
       _cons |   38.73679   .0867622   446.47   0.000     38.56487    38.90872
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_period3

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period3 if period3 != ., absorb(table_code_el
> ectionspecific) cluster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 4.period3 omitted because of collinearity

HDFE Linear regression                            Number of obs   =        420
Absorbing 1 HDFE group                            F(   4,    111) =    1152.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9395
                                                  Adj R-squared   =     0.9166
                                                  Within R-sq.    =     0.9326
Number of clusters (table_code_electionspecific) =        112Root MSE=     3.25
> 37

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -23.03427   .5911805   -38.96   0.000    -24.20574   -21.86281
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -4.079396   .8706727    -4.69   0.000    -5.804693     -2.3541
             |
     period3 |
          2  |  -1.062957    .580322    -1.83   0.070    -2.212904    .0869894
          3  |  -17.43588    .586264   -29.74   0.000     -18.5976   -16.27416
          4  |          0  (omitted)
             |
       _cons |   45.50389   .4246202   107.16   0.000     44.66248     46.3453
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_period3

. 
. * Grouping 2004 and 2007 together
. * Pre vs. post
. reghdfe pp_voteshare post##ep if period2 != ., absorb(table_code_electionspec
> ific) cluster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity

HDFE Linear regression                            Number of obs   =        448
Absorbing 1 HDFE group                            F(   2,    111) =    1195.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5629
                                                  Adj R-squared   =     0.4151
                                                  Within R-sq.    =     0.5157
Number of clusters (table_code_electionspecific) =        112Root MSE=     8.84
> 95

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -17.19974    .420358   -40.92   0.000    -18.03271   -16.36678
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -3.747646   .8882965    -4.22   0.000    -5.507865   -1.987427
             |
       _cons |   39.62417   .0927589   427.17   0.000     39.44037    39.80798
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store prepost_period2

. 
. * Fixed effects for each period
. reghdfe pp_voteshare post##ep i.period2 if period2 != ., absorb(table_code_el
> ectionspecific) cluster(table_code_electionspecific)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 4.period2 omitted because of collinearity

HDFE Linear regression                            Number of obs   =        448
Absorbing 1 HDFE group                            F(   4,    111) =    1047.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9384
                                                  Adj R-squared   =     0.9171
                                                  Within R-sq.    =     0.9318
Number of clusters (table_code_electionspecific) =        112Root MSE=     3.33
> 13

          (Std. err. adjusted for 112 clusters in table_code_electionspecific)
------------------------------------------------------------------------------
             |               Robust
pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
      1.post |  -23.86365   .6058719   -39.39   0.000    -25.06423   -22.66308
        1.ep |          0  (omitted)
             |
     post#ep |
        1 1  |  -3.747646   .8902995    -4.21   0.000    -5.511834   -1.983458
             |
     period2 |
          2  |  -1.809397   .4674134    -3.87   0.000    -2.735607   -.8831857
          3  |  -18.18232   .5013171   -36.27   0.000    -19.17572   -17.18893
          4  |          0  (omitted)
             |
       _cons |   46.28808   .3440756   134.53   0.000     45.60627    46.96989
------------------------------------------------------------------------------

Absorbed degrees of freedom:
---------------------------------------------------------------------+
                 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-----------------------------+---------------------------------------|
 table_code_electionspecific |       112         112           0    *|
---------------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. est store threeperiods_period2

. 
. * Make table
. esttab prepost_period3 threeperiods_period3 prepost_period2 threeperiods_peri
> od2 using 03_tables/tabled12.tex, tex se replace mtitles ("2003-2019" "2003-2
> 019" "2004-2019" "2004-2015")  keep (1.post 1.post#1.ep 2.period2 3.period2 2
> .period3 3.period3) coeflabels (1.post#1.ep "Treatment (absence of booth)" ep
>  "European election" 1.post "2019" 2.period2 "2009-11" 3.period2 "2014-15" 2.
> period3 "2009-11" 3.period3 "2014-15") star(* 0.10 ** 0.05 *** 0.01) addnotes
> ("All models include voting station * election type fixed effects" "Standard 
> errors are clustered by voting station * election type")
(output written to 03_tables/tabled12.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tabled13.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Generate interactions
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
(2,957 missing values generated)

. gen cabine_use_cs_dummy = cabine_use * cs_dummy
(2,960 missing values generated)

. gen cabine_use_vox_dummy = cabine_use * vox_dummy
(2,960 missing values generated)

. gen cabine_use_up_dummy = cabine_use * podemos_dummy
(2,960 missing values generated)

. gen cabine_use_psoe_dummy = cabine_use * psoe_dummy
(2,960 missing values generated)

. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_
> dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_du
> mmy cabine_use_psoe_dummy ///
> , r

Linear regression                               Number of obs     =      1,843
                                                F(11, 1831)       =       1.66
                                                Prob > F          =     0.0775
                                                R-squared         =     0.0097
                                                Root MSE          =     .30288

-------------------------------------------------------------------------------
--------
                      |               Robust
        uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. i
> nterval]
----------------------+--------------------------------------------------------
--------
           cabine_use |  -.0328764   .0321041    -1.02   0.306    -.0958409    
>  .030088
             pp_dummy |  -.0168462   .0307426    -0.55   0.584    -.0771405    
> .0434481
             cs_dummy |   .0193826   .0400044     0.48   0.628    -.0590766    
> .0978417
            vox_dummy |  -.0044077   .0316282    -0.14   0.889    -.0664388    
> .0576233
        podemos_dummy |  -.0012255   .0282516    -0.04   0.965    -.0566343    
> .0541833
           psoe_dummy |   .0273205   .0270791     1.01   0.313    -.0257887    
> .0804298
  cabine_use_pp_dummy |   .1292671   .0516341     2.50   0.012     .0279992    
> .2305351
  cabine_use_cs_dummy |  -.0216525   .0555296    -0.39   0.697    -.1305606    
> .0872555
 cabine_use_vox_dummy |   .0710324   .0501891     1.42   0.157    -.0274015    
> .1694664
  cabine_use_up_dummy |  -.0026774   .0431456    -0.06   0.951    -.0872972    
> .0819424
cabine_use_psoe_dummy |    .029374   .0428827     0.68   0.493    -.0547302    
> .1134781
                _cons |   .0931174   .0185507     5.02   0.000     .0567346    
> .1295002
-------------------------------------------------------------------------------
--------

. est store uncomf_nocontrols_all

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local FE "No"

added macro:
                 e(FE) : "No"

. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_
> dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_du
> mmy cabine_use_psoe_dummy ///
> i.CCAA, r

Linear regression                               Number of obs     =      1,843
                                                F(29, 1813)       =       2.96
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0427
                                                Root MSE          =     .29928

-------------------------------------------------------------------------------
----------------
                              |               Robust
                uncomfortable | Coefficient  std. err.      t    P>|t|     [95%
>  con                                                                         
>     f. interval]
------------------------------+------------------------------------------------
----------------
                   cabine_use |  -.0489403   .0338926    -1.44   0.149    -.115
> 4129                                                                         
>         .0175323
                     pp_dummy |  -.0612672   .0350222    -1.75   0.080    -.129
> 9552                                                                         
>         .0074209
                     cs_dummy |  -.0176225    .040701    -0.43   0.665    -.097
> 4482                                                                         
>         .0622032
                    vox_dummy |  -.0478195   .0361432    -1.32   0.186    -.118
> 7061                                                                         
>         .0230671
                podemos_dummy |  -.0470035   .0326646    -1.44   0.150    -.111
> 0676                                                                         
>         .0170607
                   psoe_dummy |  -.0100323   .0302314    -0.33   0.740    -.069
> 3243                                                                         
>         .0492597
          cabine_use_pp_dummy |   .1407423   .0522881     2.69   0.007     .038
> 1909                                                                         
>         .2432936
          cabine_use_cs_dummy |  -.0156648   .0564479    -0.28   0.781    -.126
> 3746                                                                         
>          .095045
         cabine_use_vox_dummy |    .079997   .0512018     1.56   0.118    -.020
> 4237                                                                         
>         .1804178
          cabine_use_up_dummy |   .0244346   .0444438     0.55   0.583    -.062
> 7318                                                                         
>         .1116011
        cabine_use_psoe_dummy |   .0468537   .0432227     1.08   0.279    -.037
> 9178                                                                         
>         .1316253
                              |
                         CCAA |
                      Aragón  |  -.0280734   .0394129    -0.71   0.476    -.105
> 3729                                                                         
>          .049226
    Asturias (Principado de)  |   .0946948   .0555969     1.70   0.089    -.014
> 3459                                                                         
>         .2037355
             Balears (Illes)  |   .0091112   .0428504     0.21   0.832    -.074
> 9301                                                                         
>         .0931526
                    Canarias  |  -.0523523   .0387483    -1.35   0.177    -.128
> 3483                                                                         
>         .0236437
                   Cantabria  |  -.0306788   .0378104    -0.81   0.417    -.104
> 8353                                                                         
>         .0434777
          Castilla-La Mancha  |   .1298005   .0586363     2.21   0.027     .014
> 7987                                                                         
>         .2448023
             Castilla y León  |   .0926454   .0507302     1.83   0.068    -.006
> 8503                                                                         
>         .1921411
                    Cataluña  |  -.0714654   .0290897    -2.46   0.014    -.128
> 5182                                                                         
>        -.0144126
        Comunitat Valenciana  |  -.0840916   .0252205    -3.33   0.001    -.133
> 5559                                                                         
>        -.0346273
                 Extremadura  |  -.0232545    .040442    -0.58   0.565    -.102
> 5723                                                                         
>         .0560632
                     Galicia  |  -.0541703   .0330914    -1.64   0.102    -.119
> 0716                                                                         
>          .010731
       Madrid (Comunidad de)  |   .0010469   .0300927     0.03   0.972     -.05
> 7973                                                                         
>         .0600669
          Murcia (Región de)  |  -.1096253   .0247846    -4.42   0.000    -.158
> 2348                                                                         
>        -.0610159
Navarra (Comunidad Foral de)  |   .0300629   .0601866     0.50   0.617    -.087
> 9795                                                                         
>         .1481052
                  País Vasco  |  -.0886425   .0315086    -2.81   0.005    -.150
> 4395                                                                         
>        -.0268455
                  Rioja (La)  |   -.039622   .0409641    -0.97   0.334    -.119
> 9638                                                                         
>         .0407197
  Ceuta (Ciudad Autónoma de)  |   .0360174   .0672291     0.54   0.592    -.095
> 8372                                                                         
>          .167872
Melilla (Ciudad Autónoma de)  |  -.0779776    .065413    -1.19   0.233    -.206
> 2704                                                                         
>         .0503151
                              |
                        _cons |    .147763   .0319257     4.63   0.000      .08
> 5148                                                                         
>          .210378
-------------------------------------------------------------------------------
----------------

. est store uncomf_fe_all

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. estadd local FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_
> dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_du
> mmy cabine_use_psoe_dummy ///
> female i.income i.TAMUNI age age_sq i.education, r

Linear regression                               Number of obs     =      1,352
                                                F(35, 1316)       =       2.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0397
                                                Root MSE          =     .28459

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |   -.062219   .0365038    -1.70   0.089     -.
> 133831                                                                       
>            .009393
                       pp_dummy |   -.039187   .0375896    -1.04   0.297     -.
> 112929                                                                       
>           .0345551
                       cs_dummy |   .0207302   .0501177     0.41   0.679    -.0
> 775891                                                                       
>           .1190494
                      vox_dummy |  -.0076771   .0403518    -0.19   0.849    -.0
> 868381                                                                       
>           .0714838
                  podemos_dummy |  -.0098559   .0350708    -0.28   0.779    -.0
> 786567                                                                       
>            .058945
                     psoe_dummy |  -.0047778   .0331048    -0.14   0.885    -.0
> 697217                                                                       
>           .0601661
            cabine_use_pp_dummy |    .146309   .0573508     2.55   0.011       
>  .0338                                                                       
>           .2588179
            cabine_use_cs_dummy |  -.0390384   .0607741    -0.64   0.521    -.1
> 582631                                                                       
>           .0801862
           cabine_use_vox_dummy |   .0550807    .056247     0.98   0.328    -.0
> 552629                                                                       
>           .1654242
            cabine_use_up_dummy |   .0192804   .0475354     0.41   0.685    -.0
> 739731                                                                       
>           .1125339
          cabine_use_psoe_dummy |   .0509321   .0477899     1.07   0.287    -.0
> 428205                                                                       
>           .1446848
                         female |    .030037   .0161056     1.87   0.062    -.0
> 015584                                                                       
>           .0616324
                                |
                         income |
         Menos o igual a 300 €  |   .0286401   .0643067     0.45   0.656    -.0
> 975146                                                                       
>           .1547949
                De 301 a 600 €  |   .0692304   .0415771     1.67   0.096    -.0
> 123342                                                                       
>           .1507951
                De 601 a 900 €  |   .0069631   .0309496     0.22   0.822    -.0
> 537529                                                                       
>            .067679
              De 901 a 1.200 €  |   .0153031   .0292933     0.52   0.601    -.0
> 421635                                                                       
>           .0727697
            De 1.201 a 1.800 €  |   .0131808    .027731     0.48   0.635    -.0
> 412209                                                                       
>           .0675825
            De 1.801 a 2.400 €  |  -.0352307   .0291083    -1.21   0.226    -.0
> 923345                                                                       
>            .021873
            De 2.401 a 3.000 €  |  -.0176084   .0424095    -0.42   0.678     -.
> 100806                                                                       
>           .0655892
            De 3.001 a 4.500 €  |   .0746578   .0705705     1.06   0.290    -.0
> 637852                                                                       
>           .2131008
            De 4.501 a 6.000 €  |  -.0868425   .0402415    -2.16   0.031    -.1
> 657871                                                                       
>          -.0078979
                Más de 6.000 €  |  -.0816489    .033045    -2.47   0.014    -.1
> 464755                                                                       
>          -.0168222
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0596707   .0376816     1.58   0.114     -.
> 014252                                                                       
>           .1335933
    10.001 a 50.000 habitantes  |   .0188846   .0325376     0.58   0.562    -.0
> 449466                                                                       
>           .0827158
   50.001 a 100.000 habitantes  |    .033204   .0371568     0.89   0.372     -.
> 039689                                                                       
>            .106097
  100.001 a 400.000 habitantes  |   .0027686    .032824     0.08   0.933    -.0
> 616246                                                                       
>           .0671617
400.001 a 1.000.000 habitantes  |  -.0507011   .0326853    -1.55   0.121    -.1
> 148221                                                                       
>             .01342
   Más de 1.000.000 habitantes  |  -.0459459   .0366469    -1.25   0.210    -.1
> 178386                                                                       
>           .0259468
                                |
                            age |  -.0021501   .0031799    -0.68   0.499    -.0
> 083884                                                                       
>           .0040881
                         age_sq |   .0000251   .0000336     0.75   0.456    -.0
> 000409                                                                       
>           .0000911
                                |
                      education |
                      Primaria  |  -.0787254   .0910407    -0.86   0.387    -.2
> 573261                                                                       
>           .0998753
           Secundaria 1ª etapa  |  -.0436379   .0923753    -0.47   0.637    -.2
> 248568                                                                       
>            .137581
           Secundaria 2ª etapa  |  -.0893426   .0924903    -0.97   0.334    -.2
> 707872                                                                       
>            .092102
                          F.P.  |  -.0817001    .092268    -0.89   0.376    -.2
> 627085                                                                       
>           .0993083
                    Superiores  |   -.072853   .0924837    -0.79   0.431    -.2
> 542846                                                                       
>           .1085786
                                |
                          _cons |   .1806946   .1104606     1.64   0.102    -.0
> 360034                                                                       
>           .3973927
-------------------------------------------------------------------------------
------------------

. est store uncomf_controls_all

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local FE "No"

added macro:
                 e(FE) : "No"

. 
. regr uncomfortable cabine_use pp_dummy cs_dummy vox_dummy podemos_dummy psoe_
> dummy ///
> cabine_use_pp_dummy cabine_use_cs_dummy cabine_use_vox_dummy cabine_use_up_du
> mmy cabine_use_psoe_dummy ///
> female i.income i.TAMUNI age age_sq i.education i.CCAA, r

Linear regression                               Number of obs     =      1,352
                                                F(53, 1298)       =       2.03
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0809
                                                Root MSE          =     .28035

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0524849   .0369894    -1.42   0.156    -.1
> 250504                                                                       
>           .0200806
                       pp_dummy |  -.0591206   .0397095    -1.49   0.137    -.1
> 370225                                                                       
>           .0187812
                       cs_dummy |  -.0005045   .0491396    -0.01   0.992    -.0
> 969062                                                                       
>           .0958973
                      vox_dummy |   -.029682   .0437098    -0.68   0.497    -.1
> 154315                                                                       
>           .0560676
                  podemos_dummy |  -.0296962    .036813    -0.81   0.420    -.1
> 019156                                                                       
>           .0425233
                     psoe_dummy |  -.0230886   .0355828    -0.65   0.517    -.0
> 928947                                                                       
>           .0467176
            cabine_use_pp_dummy |   .1431965   .0565183     2.53   0.011     .0
> 323193                                                                       
>           .2540737
            cabine_use_cs_dummy |  -.0391424   .0615312    -0.64   0.525     -.
> 159854                                                                       
>           .0815691
           cabine_use_vox_dummy |   .0517806    .056467     0.92   0.359     -.
> 058996                                                                       
>           .1625573
            cabine_use_up_dummy |   .0334828   .0482393     0.69   0.488    -.0
> 611528                                                                       
>           .1281184
          cabine_use_psoe_dummy |   .0663712   .0482773     1.37   0.169    -.0
> 283389                                                                       
>           .1610814
                         female |   .0293904   .0158499     1.85   0.064    -.0
> 017038                                                                       
>           .0604845
                                |
                         income |
         Menos o igual a 300 €  |   .0235038   .0650166     0.36   0.718    -.1
> 040453                                                                       
>            .151053
                De 301 a 600 €  |   .0821234   .0407727     2.01   0.044     .0
> 021357                                                                       
>           .1621111
                De 601 a 900 €  |   .0115922   .0306008     0.38   0.705    -.0
> 484402                                                                       
>           .0716247
              De 901 a 1.200 €  |   .0123337   .0281737     0.44   0.662    -.0
> 429373                                                                       
>           .0676046
            De 1.201 a 1.800 €  |   .0089293   .0279396     0.32   0.749    -.0
> 458824                                                                       
>           .0637411
            De 1.801 a 2.400 €  |  -.0351712   .0301679    -1.17   0.244    -.0
> 943544                                                                       
>            .024012
            De 2.401 a 3.000 €  |  -.0290018   .0424282    -0.68   0.494    -.1
> 122371                                                                       
>           .0542336
            De 3.001 a 4.500 €  |   .0717086   .0666299     1.08   0.282    -.0
> 590055                                                                       
>           .2024228
            De 4.501 a 6.000 €  |  -.0789769   .0551248    -1.43   0.152    -.1
> 871204                                                                       
>           .0291665
                Más de 6.000 €  |  -.0829373   .0408216    -2.03   0.042    -.1
> 630208                                                                       
>          -.0028538
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0534677   .0373177     1.43   0.152     -.
> 019742                                                                       
>           .1266774
    10.001 a 50.000 habitantes  |   .0212313   .0325786     0.65   0.515    -.0
> 426811                                                                       
>           .0851437
   50.001 a 100.000 habitantes  |    .004822   .0378757     0.13   0.899    -.0
> 694823                                                                       
>           .0791263
  100.001 a 400.000 habitantes  |  -.0086619   .0337595    -0.26   0.798    -.0
> 748911                                                                       
>           .0575674
400.001 a 1.000.000 habitantes  |  -.0364614   .0366793    -0.99   0.320    -.1
> 084186                                                                       
>           .0354958
   Más de 1.000.000 habitantes  |  -.1061079   .0428795    -2.47   0.013    -.1
> 902287                                                                       
>          -.0219872
                                |
                            age |  -.0011929   .0031376    -0.38   0.704    -.0
> 073483                                                                       
>           .0049626
                         age_sq |   .0000164   .0000332     0.49   0.622    -.0
> 000488                                                                       
>           .0000816
                                |
                      education |
                      Primaria  |  -.0709753    .092939    -0.76   0.445    -.2
> 533024                                                                       
>           .1113518
           Secundaria 1ª etapa  |  -.0327749   .0953002    -0.34   0.731    -.2
> 197341                                                                       
>           .1541844
           Secundaria 2ª etapa  |  -.0808576   .0955263    -0.85   0.397    -.2
> 682605                                                                       
>           .1065453
                          F.P.  |  -.0693122   .0952458    -0.73   0.467    -.2
> 561647                                                                       
>           .1175403
                    Superiores  |  -.0632318   .0956643    -0.66   0.509    -.2
> 509055                                                                       
>           .1244418
                                |
                           CCAA |
                        Aragón  |   -.023663   .0368071    -0.64   0.520    -.0
> 958709                                                                       
>           .0485449
      Asturias (Principado de)  |   .0626174   .0550818     1.14   0.256    -.0
> 454417                                                                       
>           .1706765
               Balears (Illes)  |   .0517605    .051799     1.00   0.318    -.0
> 498585                                                                       
>           .1533794
                      Canarias  |  -.0560818   .0344789    -1.63   0.104    -.1
> 237223                                                                       
>           .0115587
                     Cantabria  |  -.0346803   .0372351    -0.93   0.352    -.1
> 077279                                                                       
>           .0383673
            Castilla-La Mancha  |   .1316834   .0605627     2.17   0.030      .
> 012872                                                                       
>           .2504949
               Castilla y León  |   .0864184   .0553725     1.56   0.119     -.
> 022211                                                                       
>           .1950478
                      Cataluña  |  -.0007122   .0372707    -0.02   0.985    -.0
> 738295                                                                       
>           .0724051
          Comunitat Valenciana  |  -.0545316   .0281097    -1.94   0.053     -.
> 109677                                                                       
>           .0006138
                   Extremadura  |   -.016347   .0436031    -0.37   0.708    -.1
> 018872                                                                       
>           .0691933
                       Galicia  |  -.0941473   .0288171    -3.27   0.001    -.1
> 506804                                                                       
>          -.0376142
         Madrid (Comunidad de)  |    .100575   .0419995     2.39   0.017     .0
> 181807                                                                       
>           .1829694
            Murcia (Región de)  |  -.0658899   .0258598    -2.55   0.011    -.1
> 166215                                                                       
>          -.0151584
  Navarra (Comunidad Foral de)  |  -.0185987   .0589216    -0.32   0.752    -.1
> 341907                                                                       
>           .0969933
                    País Vasco  |  -.0634331   .0371961    -1.71   0.088    -.1
> 364041                                                                       
>           .0095379
                    Rioja (La)  |  -.0896216    .026442    -3.39   0.001    -.1
> 414953                                                                       
>          -.0377479
    Ceuta (Ciudad Autónoma de)  |   .0911016   .0824632     1.10   0.269     -.
> 070674                                                                       
>           .2528773
  Melilla (Ciudad Autónoma de)  |  -.0342286   .0662299    -0.52   0.605     -.
> 164158                                                                       
>           .0957008
                                |
                          _cons |   .1627692   .1165019     1.40   0.163    -.0
> 657836                                                                       
>           .3913219
-------------------------------------------------------------------------------
------------------

. est store uncomf_fe_controls_all

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. estadd local FE "Yes"

added macro:
                 e(FE) : "Yes"

. 
. 
. * Make table
. esttab uncomf_nocontrols_all uncomf_controls_all uncomf_fe_all uncomf_fe_cont
> rols_all using 03_tables/tabled13.tex, tex se replace  keep (cabine_use pp_du
> mmy cabine_use_pp_dummy cs_dummy cabine_use_cs_dummy vox_dummy cabine_use_vox
> _dummy podemos_dummy cabine_use_up_dummy psoe_dummy cabine_use_psoe_dummy) co
> eflabels (cabine_use "Used a booth to vote" pp_dummy "Voted for PP" cabine_us
> e_pp_dummy "Used booth x voted PP" cs_dummy "Voted for Ciudadanos" cabine_use
> _cs_dummy "Used booth x voted Ciudadanos" vox_dummy "Voted for Vox" cabine_us
> e_vox_dummy "Used booth x voted Vox" podemos_dummy "Voted for Podemos" cabine
> _use_up_dummy "Used booth x voted Podemos" psoe_dummy "Voted for PSOE" cabine
> _use_psoe_dummy "Used booth x voted PSOE" ) star(* 0.10 ** 0.05 *** 0.01) s(C
> ontrols FE, label("Controls" "Region fixed effects")) nomtitles addnotes("Sta
> ndard errors are robust" "The outcome variable is a dummy for whether each re
> spondent showed" "signs of discomfort during the survey interview" "Models 2 
> and 4 include controls for income, education, age, age squared, size of" "res
> pondent's municipality, and a dummy for respondents identifying as female") s
> calars(e(N))
(output written to 03_tables/tabled13.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tablee1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/whole_spain.dta, clear

. 
. regr pp_voteshare post##ciutadella if period > 1

      Source |       SS           df       MS      Number of obs   =   150,634
-------------+----------------------------------   F(3, 150630)    =   2506.40
       Model |  1497568.11         3  499189.371   Prob > F        =    0.0000
    Residual |  30000312.2   150,630  199.165586   R-squared       =    0.0475
-------------+----------------------------------   Adj R-squared   =    0.0475
       Total |  31497880.3   150,633  209.103452   Root MSE        =    14.113

-------------------------------------------------------------------------------
--
   pp_voteshare | Coefficient  Std. err.      t    P>|t|     [95% conf. interva
> l]
----------------+--------------------------------------------------------------
--
         1.post |   -6.32347   .0729537   -86.68   0.000    -6.466458   -6.1804
> 82
   1.ciutadella |   .4739284   1.886634     0.25   0.802    -3.223836    4.1716
> 93
                |
post#ciutadella |
           1 1  |  -.1831933   2.668029    -0.07   0.945    -5.412476    5.0460
> 89
                |
          _cons |   27.20169   .0534745   508.69   0.000     27.09688     27.30
> 65
-------------------------------------------------------------------------------
--

. est store reverse_bandwagon_1

. 
. regr pp_voteshare post##ciutadella

      Source |       SS           df       MS      Number of obs   =   231,289
-------------+----------------------------------   F(3, 231285)    =  12546.69
       Model |  10114451.4         3  3371483.81   Prob > F        =    0.0000
    Residual |  62149744.6   231,285  268.714982   R-squared       =    0.1400
-------------+----------------------------------   Adj R-squared   =    0.1400
       Total |  72264196.1   231,288  312.442479   Root MSE        =    16.393

-------------------------------------------------------------------------------
--
   pp_voteshare | Coefficient  Std. err.      t    P>|t|     [95% conf. interva
> l]
----------------+--------------------------------------------------------------
--
         1.post |  -13.86503   .0714925  -193.94   0.000    -14.00515   -13.724
> 91
   1.ciutadella |   .6820743   1.549526     0.44   0.660    -2.354956    3.7191
> 04
                |
post#ciutadella |
           1 1  |  -.3913392    2.68381    -0.15   0.884    -5.651537    4.8688
> 58
                |
          _cons |   34.74325   .0422902   821.54   0.000     34.66037    34.826
> 14
-------------------------------------------------------------------------------
--

. est store reverse_bandwagon_2

. 
. * Make table
. esttab reverse_bandwagon_1 reverse_bandwagon_2 using 03_tables/tablee1.tex, t
> ex se replace mtitles ("2014-2019" "2009-2019") keep(_cons 1.post 1.ciutadell
> a 1.post#1.ciutadella) coeflabels (_cons "Constant" 1.post "2019" 1.ciutadell
> a "Ciutadella" 1.post#1.ciutadella "2019 x Ciutadella") star(* 0.10 ** 0.05 *
> ** 0.01)
(output written to 03_tables/tablee1.tex)

. 
end of do-file

. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Local with outcomes
. local outcomes had_doubts voted_conviction vote_decision_long_ago vote_loyalt
> y 

. 
. * Loop over these outcomes and run regressions
. foreach outcome in `outcomes'{
  2.         regr `outcome' pp_dummy female i.income age age_sq i.education i.T
> AMUNI i.CCAA, r
  3.         est store wp_`outcome'
  4. }

Linear regression                               Number of obs     =      2,479
                                                F(43, 2434)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1027
                                                Root MSE          =     .40052

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     had_doubts | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |  -.0164605   .0205972    -0.80   0.424    -.0
> 568502                                                                       
>           .0239293
                         female |   .0218251   .0180055     1.21   0.226    -.0
> 134826                                                                       
>           .0571327
                                |
                         income |
         Menos o igual a 300 €  |   .0237723   .0604133     0.39   0.694    -.0
> 946945                                                                       
>            .142239
                De 301 a 600 €  |    .001571   .0341204     0.05   0.963    -.0
> 653371                                                                       
>           .0684791
                De 601 a 900 €  |  -.0034163   .0280103    -0.12   0.903    -.0
> 583427                                                                       
>           .0515101
              De 901 a 1.200 €  |  -.0182813   .0275426    -0.66   0.507    -.0
> 722908                                                                       
>           .0357281
            De 1.201 a 1.800 €  |   .0382805   .0307751     1.24   0.214    -.0
> 220675                                                                       
>           .0986286
            De 1.801 a 2.400 €  |   .0001234   .0396079     0.00   0.998    -.0
> 775453                                                                       
>           .0777921
            De 2.401 a 3.000 €  |   -.047524   .0544041    -0.87   0.382    -.1
> 542071                                                                       
>           .0591592
            De 3.001 a 4.500 €  |    .039149   .0779334     0.50   0.615    -.1
> 136736                                                                       
>           .1919716
            De 4.501 a 6.000 €  |  -.3415427   .0562504    -6.07   0.000    -.4
> 518463                                                                       
>           -.231239
                Más de 6.000 €  |  -.2525288   .0520269    -4.85   0.000    -.3
> 545503                                                                       
>          -.1505072
                                |
                            age |  -.0043537   .0025972    -1.68   0.094    -.0
> 094466                                                                       
>           .0007392
                         age_sq |  -4.18e-06   .0000241    -0.17   0.862    -.0
> 000514                                                                       
>            .000043
                                |
                      education |
                      Primaria  |  -.0115928   .0314286    -0.37   0.712    -.0
> 732224                                                                       
>           .0500367
           Secundaria 1ª etapa  |  -.0091012   .0361477    -0.25   0.801    -.0
> 799846                                                                       
>           .0617822
           Secundaria 2ª etapa  |   .0171056   .0403881     0.42   0.672    -.0
> 620931                                                                       
>           .0963042
                          F.P.  |   .0011098   .0391972     0.03   0.977    -.0
> 757535                                                                       
>            .077973
                    Superiores  |   .1233506   .0416366     2.96   0.003     .0
> 417037                                                                       
>           .2049975
                         Otros  |   .9258974   .0614611    15.06   0.000     .8
> 053759                                                                       
>           1.046419
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0008124   .0313616    -0.03   0.979    -.0
> 623105                                                                       
>           .0606857
    10.001 a 50.000 habitantes  |   .0503196   .0315438     1.60   0.111    -.0
> 115358                                                                       
>            .112175
   50.001 a 100.000 habitantes  |   .0475778   .0371208     1.28   0.200    -.0
> 252138                                                                       
>           .1203695
  100.001 a 400.000 habitantes  |   .0496361   .0334221     1.49   0.138    -.0
> 159025                                                                       
>           .1151747
400.001 a 1.000.000 habitantes  |   .0599162    .041998     1.43   0.154    -.0
> 224394                                                                       
>           .1422717
   Más de 1.000.000 habitantes  |  -.0023554   .0532891    -0.04   0.965     -.
> 106852                                                                       
>           .1021413
                                |
                           CCAA |
                        Aragón  |   .0215624   .0461735     0.47   0.641    -.0
> 689811                                                                       
>           .1121058
      Asturias (Principado de)  |  -.0314133   .0442218    -0.71   0.478    -.1
> 181295                                                                       
>           .0553029
               Balears (Illes)  |  -.0373255   .0499925    -0.75   0.455    -.1
> 353578                                                                       
>           .0607068
                      Canarias  |   .0529756   .0493257     1.07   0.283    -.0
> 437491                                                                       
>           .1497002
                     Cantabria  |  -.0563409   .0375623    -1.50   0.134    -.1
> 299982                                                                       
>           .0173164
            Castilla-La Mancha  |   .0166506   .0424658     0.39   0.695    -.0
> 666222                                                                       
>           .0999234
               Castilla y León  |   .0497715   .0456546     1.09   0.276    -.0
> 397544                                                                       
>           .1392975
                      Cataluña  |   .0614686   .0403679     1.52   0.128    -.0
> 176905                                                                       
>           .1406277
          Comunitat Valenciana  |   .0311017   .0351935     0.88   0.377    -.0
> 379105                                                                       
>            .100114
                   Extremadura  |   .0190076   .0402604     0.47   0.637    -.0
> 599406                                                                       
>           .0979557
                       Galicia  |   .0980263   .0422662     2.32   0.020     .0
> 151449                                                                       
>           .1809077
         Madrid (Comunidad de)  |   .1204135   .0419253     2.87   0.004     .0
> 382007                                                                       
>           .2026264
            Murcia (Región de)  |  -.0041556    .043323    -0.10   0.924    -.0
> 891094                                                                       
>           .0807981
  Navarra (Comunidad Foral de)  |   -.029988   .0489291    -0.61   0.540    -.1
> 259351                                                                       
>            .065959
                    País Vasco  |  -.0441743   .0465027    -0.95   0.342    -.1
> 353632                                                                       
>           .0470146
                    Rioja (La)  |  -.0910831   .0508003    -1.79   0.073    -.1
> 906993                                                                       
>           .0085331
    Ceuta (Ciudad Autónoma de)  |  -.0854626   .0684186    -1.25   0.212    -.2
> 196274                                                                       
>           .0487022
  Melilla (Ciudad Autónoma de)  |  -.2239183   .0375352    -5.97   0.000    -.2
> 975225                                                                       
>          -.1503141
                                |
                          _cons |   .3661989   .0766732     4.78   0.000     .2
> 158475                                                                       
>           .5165503
-------------------------------------------------------------------------------
------------------

Linear regression                               Number of obs     =      2,466
                                                F(43, 2421)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0600
                                                Root MSE          =     .46818

-------------------------------------------------------------------------------
------------------
                                |               Robust
               voted_conviction | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   -.013306    .024929    -0.53   0.594    -.0
> 621903                                                                       
>           .0355782
                         female |  -.0190425   .0204841    -0.93   0.353    -.0
> 592108                                                                       
>           .0211258
                                |
                         income |
         Menos o igual a 300 €  |   .0099266   .0655461     0.15   0.880    -.1
> 186057                                                                       
>           .1384588
                De 301 a 600 €  |  -.0392797   .0407392    -0.96   0.335    -.1
> 191671                                                                       
>           .0406076
                De 601 a 900 €  |  -.0043209   .0338037    -0.13   0.898    -.0
> 706081                                                                       
>           .0619664
              De 901 a 1.200 €  |  -.0056793   .0330088    -0.17   0.863    -.0
> 704078                                                                       
>           .0590491
            De 1.201 a 1.800 €  |   .0032857   .0353597     0.09   0.926    -.0
> 660527                                                                       
>            .072624
            De 1.801 a 2.400 €  |  -.0528061   .0465486    -1.13   0.257    -.1
> 440853                                                                       
>           .0384732
            De 2.401 a 3.000 €  |   .0841241   .0626097     1.34   0.179      -
> .03865                                                                       
>           .2068983
            De 3.001 a 4.500 €  |   .0751515   .0792589     0.95   0.343    -.0
> 802707                                                                       
>           .2305737
            De 4.501 a 6.000 €  |   -.049858   .2557054    -0.19   0.845     -.
> 551282                                                                       
>            .451566
                Más de 6.000 €  |   -.058128   .1994346    -0.29   0.771    -.4
> 492081                                                                       
>           .3329522
                                |
                            age |  -.0042944    .003045    -1.41   0.159    -.0
> 102655                                                                       
>           .0016767
                         age_sq |   .0000753   .0000289     2.61   0.009     .0
> 000187                                                                       
>           .0001319
                                |
                      education |
                      Primaria  |   .0028087   .0454355     0.06   0.951    -.0
> 862877                                                                       
>           .0919051
           Secundaria 1ª etapa  |   .0041483   .0491077     0.08   0.933    -.0
> 921492                                                                       
>           .1004458
           Secundaria 2ª etapa  |  -.0549503   .0528057    -1.04   0.298    -.1
> 584993                                                                       
>           .0485986
                          F.P.  |  -.0635929   .0522255    -1.22   0.223    -.1
> 660041                                                                       
>           .0388184
                    Superiores  |  -.1381458   .0542973    -2.54   0.011    -.2
> 446198                                                                       
>          -.0316718
                         Otros  |  -.7013853   .0772009    -9.09   0.000     -.
> 852772                                                                       
>          -.5499986
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0353834   .0422972     0.84   0.403     -.
> 047559                                                                       
>           .1183259
    10.001 a 50.000 habitantes  |  -.0187002   .0408764    -0.46   0.647    -.0
> 988565                                                                       
>           .0614562
   50.001 a 100.000 habitantes  |   .0134553   .0471306     0.29   0.775    -.0
> 789652                                                                       
>           .1058758
  100.001 a 400.000 habitantes  |  -.0251784   .0422186    -0.60   0.551    -.1
> 079668                                                                       
>           .0576099
400.001 a 1.000.000 habitantes  |   -.029713   .0521981    -0.57   0.569    -.1
> 320706                                                                       
>           .0726445
   Más de 1.000.000 habitantes  |   .0879347   .0605478     1.45   0.147    -.0
> 307961                                                                       
>           .2066656
                                |
                           CCAA |
                        Aragón  |  -.0553867   .0580022    -0.95   0.340    -.1
> 691258                                                                       
>           .0583523
      Asturias (Principado de)  |  -.0936143   .0546283    -1.71   0.087    -.2
> 007373                                                                       
>           .0135088
               Balears (Illes)  |  -.0320295   .0609332    -0.53   0.599    -.1
> 515161                                                                       
>           .0874572
                      Canarias  |   .0577642   .0518567     1.11   0.265     -.
> 043924                                                                       
>           .1594523
                     Cantabria  |   .0418405   .0468871     0.89   0.372    -.0
> 501025                                                                       
>           .1337835
            Castilla-La Mancha  |   -.045232   .0499211    -0.91   0.365    -.1
> 431244                                                                       
>           .0526605
               Castilla y León  |  -.1053995   .0523673    -2.01   0.044    -.2
> 080889                                                                       
>          -.0027102
                      Cataluña  |   .0419569   .0438174     0.96   0.338    -.0
> 439666                                                                       
>           .1278804
          Comunitat Valenciana  |  -.0836675   .0400837    -2.09   0.037    -.1
> 622695                                                                       
>          -.0050655
                   Extremadura  |  -.0241119    .047919    -0.50   0.615    -.1
> 180783                                                                       
>           .0698545
                       Galicia  |  -.1157326   .0494012    -2.34   0.019    -.2
> 126056                                                                       
>          -.0188596
         Madrid (Comunidad de)  |  -.0734499   .0461071    -1.59   0.111    -.1
> 638635                                                                       
>           .0169636
            Murcia (Región de)  |   .0479397    .048651     0.99   0.325    -.0
> 474622                                                                       
>           .1433416
  Navarra (Comunidad Foral de)  |  -.0273772   .0620778    -0.44   0.659    -.1
> 491083                                                                       
>           .0943539
                    País Vasco  |    .031969   .0573418     0.56   0.577    -.0
> 804751                                                                       
>            .144413
                    Rioja (La)  |   .0741935   .0676127     1.10   0.273    -.0
> 583912                                                                       
>           .2067783
    Ceuta (Ciudad Autónoma de)  |  -.0635093   .0878927    -0.72   0.470    -.2
> 358619                                                                       
>           .1088434
  Melilla (Ciudad Autónoma de)  |   .0911741   .0792009     1.15   0.250    -.0
> 641344                                                                       
>           .2464826
                                |
                          _cons |   .7414272   .0919471     8.06   0.000     .5
> 611241                                                                       
>           .9217302
-------------------------------------------------------------------------------
------------------

Linear regression                               Number of obs     =      2,483
                                                F(43, 2438)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0737
                                                Root MSE          =      .8788

-------------------------------------------------------------------------------
------------------
                                |               Robust
         vote_decision_long_ago | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0373094   .0450003     0.83   0.407    -.0
> 509333                                                                       
>           .1255521
                         female |  -.0636941   .0392707    -1.62   0.105    -.1
> 407015                                                                       
>           .0133134
                                |
                         income |
         Menos o igual a 300 €  |   .0937452   .1225484     0.76   0.444    -.1
> 465645                                                                       
>           .3340549
                De 301 a 600 €  |   .0610514   .0773994     0.79   0.430     -.
> 090724                                                                       
>           .2128269
                De 601 a 900 €  |   .0234719   .0639473     0.37   0.714    -.1
> 019248                                                                       
>           .1488686
              De 901 a 1.200 €  |   .0912524   .0629768     1.45   0.147    -.0
> 322411                                                                       
>            .214746
            De 1.201 a 1.800 €  |  -.0250588   .0677477    -0.37   0.712    -.1
> 579078                                                                       
>           .1077901
            De 1.801 a 2.400 €  |  -.0333557   .0870574    -0.38   0.702    -.2
> 040697                                                                       
>           .1373584
            De 2.401 a 3.000 €  |   .1467836   .1152939     1.27   0.203    -.0
> 793005                                                                       
>           .3728677
            De 3.001 a 4.500 €  |  -.0909299   .1804147    -0.50   0.614    -.4
> 447118                                                                       
>            .262852
            De 4.501 a 6.000 €  |    .602171   .1127131     5.34   0.000     .3
> 811477                                                                       
>           .8231944
                Más de 6.000 €  |   .0570236   .2724336     0.21   0.834    -.4
> 772018                                                                       
>           .5912489
                                |
                            age |   .0077882   .0058207     1.34   0.181    -.0
> 036258                                                                       
>           .0192023
                         age_sq |   .0000265    .000054     0.49   0.624    -.0
> 000794                                                                       
>           .0001324
                                |
                      education |
                      Primaria  |   .0276719   .0722838     0.38   0.702    -.1
> 140722                                                                       
>           .1694159
           Secundaria 1ª etapa  |   .0277336   .0829494     0.33   0.738    -.1
> 349251                                                                       
>           .1903922
           Secundaria 2ª etapa  |   .0077288    .090411     0.09   0.932    -.1
> 695616                                                                       
>           .1850191
                          F.P.  |   .0531507   .0878092     0.61   0.545    -.1
> 190377                                                                       
>            .225339
                    Superiores  |  -.0370052   .0914283    -0.40   0.686    -.2
> 162905                                                                       
>             .14228
                         Otros  |  -2.553814   .1341099   -19.04   0.000    -2.
> 816795                                                                       
>          -2.290833
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .027429   .0737666     0.37   0.710    -.1
> 172227                                                                       
>           .1720806
    10.001 a 50.000 habitantes  |   -.093676   .0724188    -1.29   0.196    -.2
> 356848                                                                       
>           .0483328
   50.001 a 100.000 habitantes  |  -.0751089   .0844708    -0.89   0.374    -.2
> 407509                                                                       
>           .0905331
  100.001 a 400.000 habitantes  |  -.0942394   .0760359    -1.24   0.215     -.
> 243341                                                                       
>           .0548623
400.001 a 1.000.000 habitantes  |  -.1353231    .093223    -1.45   0.147    -.3
> 181275                                                                       
>           .0474813
   Más de 1.000.000 habitantes  |   .1421195   .1138771     1.25   0.212    -.0
> 811863                                                                       
>           .3654253
                                |
                           CCAA |
                        Aragón  |  -.0095541   .1017308    -0.09   0.925    -.2
> 090418                                                                       
>           .1899337
      Asturias (Principado de)  |   .0953281   .0941356     1.01   0.311    -.0
> 892659                                                                       
>           .2799221
               Balears (Illes)  |   .0966644   .1047751     0.92   0.356    -.1
> 087929                                                                       
>           .3021218
                      Canarias  |  -.0061724   .1065461    -0.06   0.954    -.2
> 151028                                                                       
>           .2027579
                     Cantabria  |   .0078104   .0847582     0.09   0.927    -.1
> 583951                                                                       
>           .1740159
            Castilla-La Mancha  |  -.0086873   .0940474    -0.09   0.926    -.1
> 931084                                                                       
>           .1757338
               Castilla y León  |  -.0286177    .099057    -0.29   0.773    -.2
> 228622                                                                       
>           .1656269
                      Cataluña  |  -.0044396   .0800586    -0.06   0.956    -.1
> 614294                                                                       
>           .1525502
          Comunitat Valenciana  |  -.1025618   .0808644    -1.27   0.205    -.2
> 611319                                                                       
>           .0560082
                   Extremadura  |  -.0173001   .0898435    -0.19   0.847    -.1
> 934775                                                                       
>           .1588773
                       Galicia  |  -.2510739   .0971243    -2.59   0.010    -.4
> 415287                                                                       
>          -.0606192
         Madrid (Comunidad de)  |  -.2346363   .0967051    -2.43   0.015    -.4
> 242689                                                                       
>          -.0450037
            Murcia (Región de)  |   .1606886   .0873824     1.84   0.066    -.0
> 106628                                                                       
>             .33204
  Navarra (Comunidad Foral de)  |  -.0365213   .1161293    -0.31   0.753    -.2
> 642436                                                                       
>            .191201
                    País Vasco  |   .1353471   .0999293     1.35   0.176     -.
> 060608                                                                       
>           .3313022
                    Rioja (La)  |    .070583   .1381814     0.51   0.610    -.2
> 003821                                                                       
>           .3415481
    Ceuta (Ciudad Autónoma de)  |   .1614988   .1547437     1.04   0.297    -.1
> 419438                                                                       
>           .4649415
  Melilla (Ciudad Autónoma de)  |   .3146516   .1201321     2.62   0.009     .0
> 790801                                                                       
>           .5502231
                                |
                          _cons |   3.104145   .1732546    17.92   0.000     2.
> 764403                                                                       
>           3.443886
-------------------------------------------------------------------------------
------------------

Linear regression                               Number of obs     =      2,445
                                                F(43, 2400)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1404
                                                Root MSE          =     .79361

-------------------------------------------------------------------------------
------------------
                                |               Robust
                   vote_loyalty | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1253854   .0432816     2.90   0.004     .0
> 405121                                                                       
>           .2102586
                         female |   .0498992   .0352964     1.41   0.158    -.0
> 193154                                                                       
>           .1191137
                                |
                         income |
         Menos o igual a 300 €  |   .1351738   .1090908     1.24   0.215    -.0
> 787482                                                                       
>           .3490958
                De 301 a 600 €  |   .1199886   .0700885     1.71   0.087    -.0
> 174517                                                                       
>            .257429
                De 601 a 900 €  |   .0655496   .0577811     1.13   0.257    -.0
> 477565                                                                       
>           .1788557
              De 901 a 1.200 €  |   .0580927    .056804     1.02   0.307    -.0
> 532973                                                                       
>           .1694826
            De 1.201 a 1.800 €  |  -.0033683   .0590938    -0.06   0.955    -.1
> 192484                                                                       
>           .1125119
            De 1.801 a 2.400 €  |  -.0125801   .0798656    -0.16   0.875    -.1
> 691927                                                                       
>           .1440325
            De 2.401 a 3.000 €  |   .0160388   .1059681     0.15   0.880    -.1
> 917596                                                                       
>           .2238372
            De 3.001 a 4.500 €  |   -.132591   .1298368    -1.02   0.307    -.3
> 871947                                                                       
>           .1220128
            De 4.501 a 6.000 €  |  -.6320986    .315128    -2.01   0.045     -1
> .25005                                                                       
>          -.0141474
                Más de 6.000 €  |     .09923    .362486     0.27   0.784     -.
> 611588                                                                       
>           .8100479
                                |
                            age |  -.0029693   .0053553    -0.55   0.579    -.0
> 134708                                                                       
>           .0075322
                         age_sq |   .0001363   .0000515     2.65   0.008     .0
> 000354                                                                       
>           .0002372
                                |
                      education |
                      Primaria  |   .0137607   .0832482     0.17   0.869    -.1
> 494851                                                                       
>           .1770065
           Secundaria 1ª etapa  |  -.0456737   .0889037    -0.51   0.607    -.2
> 200097                                                                       
>           .1286623
           Secundaria 2ª etapa  |  -.1365769   .0954809    -1.43   0.153    -.3
> 238105                                                                       
>           .0506567
                          F.P.  |  -.1986378   .0937395    -2.12   0.034    -.3
> 824565                                                                       
>          -.0148192
                    Superiores  |  -.2544921   .0962283    -2.64   0.008    -.4
> 431911                                                                       
>           -.065793
                         Otros  |   -1.38941   .1356837   -10.24   0.000     -1
> .65548                                                                       
>          -1.123341
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0331484   .0723608     0.46   0.647    -.1
> 087478                                                                       
>           .1750445
    10.001 a 50.000 habitantes  |    -.07821   .0697651    -1.12   0.262    -.2
> 150162                                                                       
>           .0585962
   50.001 a 100.000 habitantes  |   -.094625   .0806426    -1.17   0.241    -.2
> 527613                                                                       
>           .0635113
  100.001 a 400.000 habitantes  |  -.0642667   .0717316    -0.90   0.370     -.
> 204929                                                                       
>           .0763956
400.001 a 1.000.000 habitantes  |  -.0624925   .0891339    -0.70   0.483      -
> .23728                                                                       
>           .1122949
   Más de 1.000.000 habitantes  |   .0627153   .1047392     0.60   0.549    -.1
> 426733                                                                       
>           .2681039
                                |
                           CCAA |
                        Aragón  |  -.1100582   .0985329    -1.12   0.264    -.3
> 032766                                                                       
>           .0831602
      Asturias (Principado de)  |  -.0695981   .0862335    -0.81   0.420    -.2
> 386979                                                                       
>           .0995018
               Balears (Illes)  |   -.046332   .1015685    -0.46   0.648     -.
> 245503                                                                       
>            .152839
                      Canarias  |  -.1634409    .090335    -1.81   0.071    -.3
> 405837                                                                       
>           .0137018
                     Cantabria  |  -.0592833   .0839935    -0.71   0.480    -.2
> 239906                                                                       
>            .105424
            Castilla-La Mancha  |  -.1521425   .0863404    -1.76   0.078     -.
> 321452                                                                       
>            .017167
               Castilla y León  |  -.1219659   .0861243    -1.42   0.157    -.2
> 908515                                                                       
>           .0469198
                      Cataluña  |  -.1120693   .0772224    -1.45   0.147    -.2
> 634987                                                                       
>           .0393601
          Comunitat Valenciana  |  -.2283466   .0650566    -3.51   0.000    -.3
> 559195                                                                       
>          -.1007737
                   Extremadura  |  -.2489714   .0796625    -3.13   0.002    -.4
> 051858                                                                       
>          -.0927569
                       Galicia  |   -.135867   .0829575    -1.64   0.102    -.2
> 985428                                                                       
>           .0268087
         Madrid (Comunidad de)  |  -.2517397   .0735735    -3.42   0.001    -.3
> 960138                                                                       
>          -.1074656
            Murcia (Región de)  |  -.0860024   .0931036    -0.92   0.356    -.2
> 685741                                                                       
>           .0965694
  Navarra (Comunidad Foral de)  |  -.0291129   .1133887    -0.26   0.797    -.2
> 514628                                                                       
>           .1932371
                    País Vasco  |   .3042897   .0948499     3.21   0.001     .1
> 182935                                                                       
>            .490286
                    Rioja (La)  |   .0147632   .1091712     0.14   0.892    -.1
> 993163                                                                       
>           .2288428
    Ceuta (Ciudad Autónoma de)  |   .1990249   .1479305     1.35   0.179    -.0
> 910599                                                                       
>           .4891096
  Melilla (Ciudad Autónoma de)  |   .0078408    .162815     0.05   0.962    -.3
> 114317                                                                       
>           .3271134
                                |
                          _cons |    1.99636   .1604001    12.45   0.000     1.
> 681823                                                                       
>           2.310897
-------------------------------------------------------------------------------
------------------

. 
. * Make table
. esttab wp_had_doubts wp_voted_conviction wp_vote_decision_long_ago wp_vote_lo
> yalty using 03_tables/tablee2.tex, tex se replace  keep (pp_dummy) coeflabels
>  (pp_dummy "PP voter") star(* 0.10 ** 0.05 *** 0.01) mtitles("Doubted vote ch
> oice" "Voted with conviction" "Decided vote long ago" "Loyal voter") addnotes
> ("Standard errors are robust" "All models include region fixed effects" "All 
> models include controls for income, education, age, age squared, size" " of r
> espondent's municipality, and a dummy for respondents identifying as female")
(output written to 03_tables/tablee2.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tablef1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Run analyses
. regr cabine_use cs_dummy if pp_dummy == 0, r

Linear regression                               Number of obs     =      1,586
                                                F(1, 1584)        =       0.90
                                                Prob > F          =     0.3432
                                                R-squared         =     0.0006
                                                Root MSE          =      .4947

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    cs_dummy |   .0406795   .0429047     0.95   0.343    -.0434765    .1248354
       _cons |   .4224078   .0130383    32.40   0.000     .3968336     .447982
------------------------------------------------------------------------------

. est store other_cs_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr cabine_use cs_dummy female i.income age age_sq i.education i.TAMUNI i.CC
> AA if pp_dummy == 0, r

Linear regression                               Number of obs     =      1,175
                                                F(43, 1131)       =      15.58
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2317
                                                Root MSE          =     .44519

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       cs_dummy |   .0316128   .0436451     0.72   0.469    -.0
> 540216                                                                       
>           .1172473
                         female |   .0028845   .0283148     0.10   0.919    -.0
> 526709                                                                       
>           .0584399
                                |
                         income |
         Menos o igual a 300 €  |  -.0508062   .1026511    -0.49   0.621    -.2
> 522142                                                                       
>           .1506017
                De 301 a 600 €  |   .0002955   .0623802     0.00   0.996    -.1
> 220984                                                                       
>           .1226893
                De 601 a 900 €  |   -.032685   .0495625    -0.66   0.510    -.1
> 299297                                                                       
>           .0645597
              De 901 a 1.200 €  |   -.038019   .0465204    -0.82   0.414     -.
> 129295                                                                       
>            .053257
            De 1.201 a 1.800 €  |  -.0189407   .0495739    -0.38   0.702    -.1
> 162078                                                                       
>           .0783263
            De 1.801 a 2.400 €  |   .0237487   .0587652     0.40   0.686    -.0
> 915523                                                                       
>           .1390497
            De 2.401 a 3.000 €  |  -.0478802     .08504    -0.56   0.574     -.
> 214734                                                                       
>           .1189737
            De 3.001 a 4.500 €  |    .206037   .1149755     1.79   0.073    -.0
> 195523                                                                       
>           .4316264
            De 4.501 a 6.000 €  |   -.420313   .1730909    -2.43   0.015    -.7
> 599283                                                                       
>          -.0806977
                Más de 6.000 €  |   .3273747   .1573354     2.08   0.038     .0
> 186726                                                                       
>           .6360769
                                |
                            age |  -.0015677   .0049341    -0.32   0.751    -.0
> 112487                                                                       
>           .0081134
                         age_sq |  -.0000107   .0000517    -0.21   0.835    -.0
> 001121                                                                       
>           .0000906
                                |
                      education |
                      Primaria  |  -.0982556   .1146598    -0.86   0.392    -.3
> 232255                                                                       
>           .1267143
           Secundaria 1ª etapa  |  -.1865224   .1165832    -1.60   0.110     -.
> 415266                                                                       
>           .0422213
           Secundaria 2ª etapa  |  -.2201027   .1181693    -1.86   0.063    -.4
> 519584                                                                       
>           .0117531
                          F.P.  |   -.150839   .1174706    -1.28   0.199    -.3
> 813238                                                                       
>           .0796457
                    Superiores  |  -.1495074   .1188233    -1.26   0.209    -.3
> 826463                                                                       
>           .0836315
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0057473   .0674969    -0.09   0.932    -.1
> 381804                                                                       
>           .1266858
    10.001 a 50.000 habitantes  |   -.113105    .064769    -1.75   0.081    -.2
> 401859                                                                       
>           .0139758
   50.001 a 100.000 habitantes  |  -.1568675   .0731393    -2.14   0.032    -.3
> 003715                                                                       
>          -.0133635
  100.001 a 400.000 habitantes  |  -.1914248    .066947    -2.86   0.004    -.3
> 227791                                                                       
>          -.0600706
400.001 a 1.000.000 habitantes  |   -.365517   .0748842    -4.88   0.000    -.5
> 124446                                                                       
>          -.2185894
   Más de 1.000.000 habitantes  |  -.2104219   .0706298    -2.98   0.003    -.3
> 490021                                                                       
>          -.0718416
                                |
                           CCAA |
                        Aragón  |  -.0174719   .0739488    -0.24   0.813    -.1
> 625641                                                                       
>           .1276202
      Asturias (Principado de)  |  -.2199781   .0760594    -2.89   0.004    -.3
> 692115                                                                       
>          -.0707447
               Balears (Illes)  |  -.1276654   .0836798    -1.53   0.127    -.2
> 918505                                                                       
>           .0365197
                      Canarias  |   .3744451   .0575534     6.51   0.000     .2
> 615216                                                                       
>           .4873686
                     Cantabria  |  -.0122935    .075913    -0.16   0.871    -.1
> 612397                                                                       
>           .1366526
            Castilla-La Mancha  |   .0047909   .0836061     0.06   0.954    -.1
> 592496                                                                       
>           .1688313
               Castilla y León  |    .051952   .0796315     0.65   0.514      -
> .10429                                                                       
>           .2081941
                      Cataluña  |  -.4249565   .0512489    -8.29   0.000    -.5
> 255102                                                                       
>          -.3244028
          Comunitat Valenciana  |  -.0530939   .0597775    -0.89   0.375    -.1
> 703811                                                                       
>           .0641934
                   Extremadura  |   .1598385   .0705721     2.26   0.024     .0
> 213715                                                                       
>           .2983054
                       Galicia  |   .0433507   .0752502     0.58   0.565     -.
> 104295                                                                       
>           .1909964
         Madrid (Comunidad de)  |  -.3691898   .0517627    -7.13   0.000    -.4
> 707515                                                                       
>          -.2676281
            Murcia (Región de)  |   .1326726   .0745816     1.78   0.076    -.0
> 136613                                                                       
>           .2790066
  Navarra (Comunidad Foral de)  |  -.1590079   .0939088    -1.69   0.091     -.
> 343263                                                                       
>           .0252471
                    País Vasco  |  -.1113218   .0917135    -1.21   0.225    -.2
> 912695                                                                       
>           .0686259
                    Rioja (La)  |  -.0623504   .1280294    -0.49   0.626    -.3
> 135522                                                                       
>           .1888514
    Ceuta (Ciudad Autónoma de)  |   .2494302   .1083203     2.30   0.021     .0
> 368989                                                                       
>           .4619615
  Melilla (Ciudad Autónoma de)  |   .1237449   .1441827     0.86   0.391    -.1
> 591509                                                                       
>           .4066406
                                |
                          _cons |   .9505243   .1557521     6.10   0.000     .6
> 449289                                                                       
>            1.25612
-------------------------------------------------------------------------------
------------------

. est store other_cs_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. regr cabine_use vox_dummy if pp_dummy == 0, r

Linear regression                               Number of obs     =      1,586
                                                F(1, 1584)        =      10.75
                                                Prob > F          =     0.0011
                                                R-squared         =     0.0069
                                                Root MSE          =     .49313

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
   vox_dummy |   .1112473   .0339247     3.28   0.001     .0447053    .1777894
       _cons |   .4081325   .0134955    30.24   0.000     .3816617    .4346034
------------------------------------------------------------------------------

. est store other_vox_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr cabine_use vox_dummy female i.income age age_sq i.education i.TAMUNI i.C
> CAA if pp_dummy == 0, r

Linear regression                               Number of obs     =      1,175
                                                F(43, 1131)       =      15.21
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2318
                                                Root MSE          =     .44517

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                      vox_dummy |   .0295126   .0384782     0.77   0.443    -.0
> 459841                                                                       
>           .1050093
                         female |   .0059264   .0283455     0.21   0.834    -.0
> 496893                                                                       
>            .061542
                                |
                         income |
         Menos o igual a 300 €  |  -.0508809   .1023432    -0.50   0.619    -.2
> 516847                                                                       
>           .1499229
                De 301 a 600 €  |   .0003865   .0623877     0.01   0.995    -.1
> 220222                                                                       
>           .1227952
                De 601 a 900 €  |  -.0345941   .0496982    -0.70   0.487    -.1
> 321051                                                                       
>           .0629169
              De 901 a 1.200 €  |  -.0398145   .0464519    -0.86   0.392    -.1
> 309561                                                                       
>           .0513271
            De 1.201 a 1.800 €  |   -.019718    .049615    -0.40   0.691    -.1
> 170658                                                                       
>           .0776297
            De 1.801 a 2.400 €  |   .0217556   .0588314     0.37   0.712    -.0
> 936753                                                                       
>           .1371865
            De 2.401 a 3.000 €  |  -.0475968   .0849538    -0.56   0.575    -.2
> 142815                                                                       
>           .1190879
            De 3.001 a 4.500 €  |   .2098285   .1152929     1.82   0.069    -.0
> 163835                                                                       
>           .4360406
            De 4.501 a 6.000 €  |  -.4409309   .1828601    -2.41   0.016    -.7
> 997141                                                                       
>          -.0821476
                Más de 6.000 €  |   .3142008    .160503     1.96   0.051    -.0
> 007163                                                                       
>            .629118
                                |
                            age |  -.0014492   .0049458    -0.29   0.770    -.0
> 111531                                                                       
>           .0082547
                         age_sq |  -.0000118   .0000517    -0.23   0.819    -.0
> 001134                                                                       
>           .0000897
                                |
                      education |
                      Primaria  |  -.0983265   .1145002    -0.86   0.391    -.3
> 229831                                                                       
>           .1263302
           Secundaria 1ª etapa  |  -.1921888   .1163673    -1.65   0.099    -.4
> 205089                                                                       
>           .0361312
           Secundaria 2ª etapa  |  -.2224657   .1179569    -1.89   0.060    -.4
> 539047                                                                       
>           .0089734
                          F.P.  |  -.1533764   .1172502    -1.31   0.191    -.3
> 834287                                                                       
>            .076676
                    Superiores  |  -.1483685   .1186615    -1.25   0.211      -
> .38119                                                                       
>           .0844529
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0049494   .0675817    -0.07   0.942     -.
> 137549                                                                       
>           .1276502
    10.001 a 50.000 habitantes  |  -.1110678    .064933    -1.71   0.087    -.2
> 384705                                                                       
>           .0163349
   50.001 a 100.000 habitantes  |  -.1584107   .0732497    -2.16   0.031    -.3
> 021312                                                                       
>          -.0146902
  100.001 a 400.000 habitantes  |   -.190426    .067002    -2.84   0.005    -.3
> 218882                                                                       
>          -.0589638
400.001 a 1.000.000 habitantes  |  -.3620563   .0748385    -4.84   0.000    -.5
> 088942                                                                       
>          -.2152184
   Más de 1.000.000 habitantes  |  -.2110209   .0707362    -2.98   0.003    -.3
> 498098                                                                       
>          -.0722321
                                |
                           CCAA |
                        Aragón  |  -.0186781    .074054    -0.25   0.801    -.1
> 639767                                                                       
>           .1266205
      Asturias (Principado de)  |  -.2227363   .0756853    -2.94   0.003    -.3
> 712357                                                                       
>          -.0742369
               Balears (Illes)  |  -.1326303   .0834163    -1.59   0.112    -.2
> 962985                                                                       
>           .0310379
                      Canarias  |   .3748759   .0576791     6.50   0.000     .2
> 617059                                                                       
>           .4880459
                     Cantabria  |  -.0114904    .075989    -0.15   0.880    -.1
> 605856                                                                       
>           .1376048
            Castilla-La Mancha  |  -.0005793   .0838799    -0.01   0.994    -.1
> 651571                                                                       
>           .1639984
               Castilla y León  |   .0508262   .0791094     0.64   0.521    -.1
> 043914                                                                       
>           .2060439
                      Cataluña  |   -.422809   .0513948    -8.23   0.000    -.5
> 236489                                                                       
>          -.3219691
          Comunitat Valenciana  |   -.055371   .0596707    -0.93   0.354    -.1
> 724488                                                                       
>           .0617067
                   Extremadura  |   .1607293   .0710272     2.26   0.024     .0
> 213695                                                                       
>           .3000892
                       Galicia  |   .0410739   .0752631     0.55   0.585     -.
> 106597                                                                       
>           .1887448
         Madrid (Comunidad de)  |  -.3693579   .0518717    -7.12   0.000    -.4
> 711334                                                                       
>          -.2675823
            Murcia (Región de)  |   .1256437   .0743131     1.69   0.091    -.0
> 201633                                                                       
>           .2714507
  Navarra (Comunidad Foral de)  |  -.1592468   .0937156    -1.70   0.090    -.3
> 431228                                                                       
>           .0246291
                    País Vasco  |  -.1114226   .0914828    -1.22   0.223    -.2
> 909177                                                                       
>           .0680725
                    Rioja (La)  |  -.0665046   .1287046    -0.52   0.605    -.3
> 190312                                                                       
>           .1860219
    Ceuta (Ciudad Autónoma de)  |    .231178   .1099298     2.10   0.036     .0
> 154886                                                                       
>           .4468673
  Melilla (Ciudad Autónoma de)  |   .1198039   .1426031     0.84   0.401    -.1
> 599925                                                                       
>           .3996003
                                |
                          _cons |   .9476276   .1561012     6.07   0.000     .6
> 413471                                                                       
>           1.253908
-------------------------------------------------------------------------------
------------------

. est store other_vox_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. * Make table (without full list of controls)
. esttab other_cs_nocontrols other_cs_controls other_vox_nocontrols other_vox_c
> ontrols using 03_tables/tablef1.tex, tex se replace keep(cs_dummy vox_dummy) 
> coeflabels (cs_dummy "Ciudadanos voter" vox_dummy "Vox voter") nomtitles star
> (* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")) addnotes("Standard e
> rrors are robust" "The outcome variable is a dummy for whether each responden
> t used a private" "voting booth to cast their vote in the general election of
>  November 2019" "Models 2 and 4 include controls for income, education, age, 
> age squared, size of" "respondent's municipality, and a dummy for respondents
>  identifying as female" "The analyses exclude respondents who voted for PP") 
> scalars(e(N))
(output written to 03_tables/tablef1.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tablef2.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Generate interactions
. gen cabine_use_cs = cabine_use * cs_dummy
(2,960 missing values generated)

. gen cabine_use_vox = cabine_use * vox_dummy
(2,960 missing values generated)

. 
. * Run analyses
. regr uncomfortable cabine_use cs_dummy cabine_use_cs if pp_dummy == 0, cluste
> r(municipality)

Linear regression                               Number of obs     =      1,586
                                                F(3, 121)         =       0.60
                                                Prob > F          =     0.6139
                                                R-squared         =     0.0010
                                                Root MSE          =     .29803

                          (Std. err. adjusted for 122 clusters in municipality)
-------------------------------------------------------------------------------
              |               Robust
uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------+----------------------------------------------------------------
   cabine_use |  -.0040055   .0195347    -0.21   0.838    -.0426796    .0346686
     cs_dummy |   .0112952   .0456465     0.25   0.805    -.0790742    .1016646
cabine_use_cs |  -.0505235   .0581328    -0.87   0.387    -.1656127    .0645657
        _cons |   .1012048   .0150045     6.74   0.000     .0714995    .1309101
-------------------------------------------------------------------------------

. est store uncomf_cs_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr uncomfortable cabine_use cs_dummy cabine_use_cs female i.income age age_
> sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, cluster(municipality)

Linear regression                               Number of obs     =      1,175
                                                F(43, 117)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0648
                                                Root MSE          =     .27653

                                            (Std. err. adjusted for 118 cluster
> s in municipality)
-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0109583   .0214749    -0.51   0.611    -.0
> 534881                                                                       
>           .0315716
                       cs_dummy |    .019332   .0558466     0.35   0.730    -.0
> 912693                                                                       
>           .1299332
                  cabine_use_cs |  -.0819299   .0665846    -1.23   0.221    -.2
> 137972                                                                       
>           .0499374
                         female |   .0321415   .0188919     1.70   0.092    -.0
> 052729                                                                       
>           .0695559
                                |
                         income |
         Menos o igual a 300 €  |   .0189942   .0661553     0.29   0.775    -.1
> 120229                                                                       
>           .1500113
                De 301 a 600 €  |    .046921   .0416627     1.13   0.262    -.0
> 355898                                                                       
>           .1294317
                De 601 a 900 €  |   .0024535   .0360349     0.07   0.946    -.0
> 689119                                                                       
>           .0738188
              De 901 a 1.200 €  |   .0070435   .0284717     0.25   0.805    -.0
> 493433                                                                       
>           .0634302
            De 1.201 a 1.800 €  |   .0197295   .0276463     0.71   0.477    -.0
> 350227                                                                       
>           .0744816
            De 1.801 a 2.400 €  |   -.030502   .0377956    -0.81   0.421    -.1
> 053541                                                                       
>           .0443502
            De 2.401 a 3.000 €  |  -.0389624   .0398977    -0.98   0.331    -.1
> 179777                                                                       
>           .0400529
            De 3.001 a 4.500 €  |   .0934068   .0959396     0.97   0.332    -.0
> 965965                                                                       
>           .2834101
            De 4.501 a 6.000 €  |  -.0879119   .0510298    -1.72   0.088    -.1
> 889737                                                                       
>             .01315
                Más de 6.000 €  |  -.0706422    .043749    -1.61   0.109    -.1
> 572849                                                                       
>           .0160005
                                |
                            age |  -.0011295   .0032877    -0.34   0.732    -.0
> 076405                                                                       
>           .0053816
                         age_sq |   .0000181   .0000364     0.50   0.619    -.0
> 000539                                                                       
>           .0000902
                                |
                      education |
                      Primaria  |  -.1122454   .1016779    -1.10   0.272    -.3
> 136132                                                                       
>           .0891224
           Secundaria 1ª etapa  |  -.0517292   .1130343    -0.46   0.648    -.2
> 755878                                                                       
>           .1721294
           Secundaria 2ª etapa  |  -.0995348   .1085185    -0.92   0.361      -
> .31445                                                                       
>           .1153804
                          F.P.  |  -.0898664    .111426    -0.81   0.422    -.3
> 105397                                                                       
>           .1308068
                    Superiores  |  -.0940855   .1102921    -0.85   0.395    -.3
> 125133                                                                       
>           .1243422
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .1056949   .0352191     3.00   0.003     .0
> 359454                                                                       
>           .1754444
    10.001 a 50.000 habitantes  |   .0620622   .0264332     2.35   0.021     .0
> 097127                                                                       
>           .1144118
   50.001 a 100.000 habitantes  |    .052379   .0401664     1.30   0.195    -.0
> 271684                                                                       
>           .1319265
  100.001 a 400.000 habitantes  |   .0328742   .0353404     0.93   0.354    -.0
> 371157                                                                       
>           .1028641
400.001 a 1.000.000 habitantes  |   .0048353   .0362831     0.13   0.894    -.0
> 670214                                                                       
>            .076692
   Más de 1.000.000 habitantes  |   -.050799   .0387284    -1.31   0.192    -.1
> 274985                                                                       
>           .0259005
                                |
                           CCAA |
                        Aragón  |  -.0408821   .0454402    -0.90   0.370     -.
> 130874                                                                       
>           .0491097
      Asturias (Principado de)  |   .0145791   .0446535     0.33   0.745    -.0
> 738548                                                                       
>           .1030131
               Balears (Illes)  |   .0267574   .0491006     0.54   0.587    -.0
> 704839                                                                       
>           .1239987
                      Canarias  |  -.0589585   .0461084    -1.28   0.204    -.1
> 502739                                                                       
>           .0323569
                     Cantabria  |  -.0270269   .0489208    -0.55   0.582    -.1
> 239119                                                                       
>           .0698582
            Castilla-La Mancha  |   .0693859    .078476     0.88   0.378    -.0
> 860318                                                                       
>           .2248035
               Castilla y León  |   .0510389   .0884237     0.58   0.565    -.1
> 240795                                                                       
>           .2261573
                      Cataluña  |  -.0060378   .0492639    -0.12   0.903    -.1
> 036025                                                                       
>           .0915268
          Comunitat Valenciana  |  -.0596884   .0532447    -1.12   0.265    -.1
> 651368                                                                       
>           .0457599
                   Extremadura  |   .0029224   .0613462     0.05   0.962    -.1
> 185704                                                                       
>           .1244153
                       Galicia  |  -.1054866   .0499624    -2.11   0.037    -.2
> 044345                                                                       
>          -.0065386
         Madrid (Comunidad de)  |   .0721006   .0580243     1.24   0.217    -.0
> 428134                                                                       
>           .1870146
            Murcia (Región de)  |  -.0692468   .0404954    -1.71   0.090    -.1
> 494458                                                                       
>           .0109521
  Navarra (Comunidad Foral de)  |  -.0215804   .0511505    -0.42   0.674    -.1
> 228813                                                                       
>           .0797205
                    País Vasco  |   -.073995   .0529582    -1.40   0.165    -.1
> 788759                                                                       
>            .030886
                    Rioja (La)  |  -.1084138   .0468306    -2.32   0.022    -.2
> 011592                                                                       
>          -.0156683
    Ceuta (Ciudad Autónoma de)  |   .0412362   .0546744     0.75   0.452    -.0
> 670436                                                                       
>            .149516
  Melilla (Ciudad Autónoma de)  |  -.0006019   .0486979    -0.01   0.990    -.0
> 970457                                                                       
>           .0958418
                                |
                          _cons |    .131299    .120757     1.09   0.279     -.
> 107854                                                                       
>            .370452
-------------------------------------------------------------------------------
------------------

. est store uncomf_cs_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. regr uncomfortable cabine_use vox_dummy cabine_use_vox if pp_dummy == 0, clus
> ter(municipality)

Linear regression                               Number of obs     =      1,586
                                                F(3, 121)         =       1.05
                                                Prob > F          =     0.3745
                                                R-squared         =     0.0018
                                                Root MSE          =     .29792

                           (Std. err. adjusted for 122 clusters in municipality
> )
-------------------------------------------------------------------------------
-
               |               Robust
 uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. interval
> ]
---------------+---------------------------------------------------------------
-
    cabine_use |  -.0194549   .0207399    -0.94   0.350    -.0605149    .021605
> 2
     vox_dummy |   -.015616   .0274926    -0.57   0.571    -.0700449    .038812
> 8
cabine_use_vox |   .0576108   .0362683     1.59   0.115    -.0141918    .129413
> 5
         _cons |   .1043257   .0174006     6.00   0.000     .0698766    .138774
> 8
-------------------------------------------------------------------------------
-

. est store uncomf_vox_nocontrols

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr uncomfortable cabine_use vox_dummy cabine_use_vox female i.income age ag
> e_sq i.education i.TAMUNI i.CCAA if pp_dummy == 0, cluster(municipality)

Linear regression                               Number of obs     =      1,175
                                                F(43, 117)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0628
                                                Root MSE          =     .27683

                                            (Std. err. adjusted for 118 cluster
> s in municipality)
-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0219421   .0219216    -1.00   0.319    -.0
> 653568                                                                       
>           .0214725
                      vox_dummy |  -.0101061    .030666    -0.33   0.742    -.0
> 708384                                                                       
>           .0506263
                 cabine_use_vox |    .020594   .0393184     0.52   0.601    -.0
> 572741                                                                       
>           .0984621
                         female |   .0305649   .0185776     1.65   0.103    -.0
> 062271                                                                       
>            .067357
                                |
                         income |
         Menos o igual a 300 €  |   .0215732   .0652708     0.33   0.742    -.1
> 076923                                                                       
>           .1508386
                De 301 a 600 €  |   .0480396   .0419215     1.15   0.254    -.0
> 349837                                                                       
>           .1310629
                De 601 a 900 €  |    .001894   .0360533     0.05   0.958    -.0
> 695077                                                                       
>           .0732957
              De 901 a 1.200 €  |   .0079146   .0286492     0.28   0.783    -.0
> 488237                                                                       
>           .0646529
            De 1.201 a 1.800 €  |    .019158   .0275637     0.70   0.488    -.0
> 354306                                                                       
>           .0737465
            De 1.801 a 2.400 €  |  -.0307867   .0381414    -0.81   0.421    -.1
> 063236                                                                       
>           .0447503
            De 2.401 a 3.000 €  |  -.0353062   .0441579    -0.80   0.426    -.1
> 227586                                                                       
>           .0521461
            De 3.001 a 4.500 €  |   .0866732   .0961551     0.90   0.369    -.1
> 037568                                                                       
>           .2771033
            De 4.501 a 6.000 €  |  -.0827838   .0571119    -1.45   0.150     -.
> 195891                                                                       
>           .0303234
                Más de 6.000 €  |   -.066292   .0444829    -1.49   0.139    -.1
> 543882                                                                       
>           .0218041
                                |
                            age |  -.0009948   .0033142    -0.30   0.765    -.0
> 075585                                                                       
>           .0055688
                         age_sq |   .0000167   .0000366     0.46   0.650    -.0
> 000559                                                                       
>           .0000893
                                |
                      education |
                      Primaria  |  -.1187613   .1013891    -1.17   0.244    -.3
> 195571                                                                       
>           .0820346
           Secundaria 1ª etapa  |  -.0577712   .1130315    -0.51   0.610    -.2
> 816242                                                                       
>           .1660818
           Secundaria 2ª etapa  |  -.1049318   .1084527    -0.97   0.335    -.3
> 197168                                                                       
>           .1098532
                          F.P.  |  -.0965871   .1116483    -0.87   0.389    -.3
> 177008                                                                       
>           .1245265
                    Superiores  |  -.1015671    .110067    -0.92   0.358    -.3
> 195491                                                                       
>           .1164149
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .1052011   .0350578     3.00   0.003     .0
> 357709                                                                       
>           .1746314
    10.001 a 50.000 habitantes  |   .0610777   .0264741     2.31   0.023     .0
> 086471                                                                       
>           .1135082
   50.001 a 100.000 habitantes  |   .0538772   .0401063     1.34   0.182    -.0
> 255511                                                                       
>           .1333055
  100.001 a 400.000 habitantes  |   .0340612   .0351833     0.97   0.335    -.0
> 356174                                                                       
>           .1037398
400.001 a 1.000.000 habitantes  |   .0055592   .0359875     0.15   0.877    -.0
> 657121                                                                       
>           .0768306
   Más de 1.000.000 habitantes  |  -.0520657   .0389415    -1.34   0.184    -.1
> 291873                                                                       
>            .025056
                                |
                           CCAA |
                        Aragón  |  -.0414917   .0452556    -0.92   0.361     -.
> 131118                                                                       
>           .0481346
      Asturias (Principado de)  |   .0115386   .0463902     0.25   0.804    -.0
> 803348                                                                       
>           .1034121
               Balears (Illes)  |   .0271391   .0482375     0.56   0.575    -.0
> 683927                                                                       
>            .122671
                      Canarias  |  -.0645757   .0478781    -1.35   0.180    -.1
> 593957                                                                       
>           .0302444
                     Cantabria  |  -.0260489   .0486385    -0.54   0.593    -.1
> 223748                                                                       
>           .0702771
            Castilla-La Mancha  |   .0672492   .0796543     0.84   0.400     -.
> 090502                                                                       
>           .2250003
               Castilla y León  |   .0512261   .0885941     0.58   0.564    -.1
> 242299                                                                       
>           .2266821
                      Cataluña  |  -.0054561   .0494343    -0.11   0.912    -.1
> 033581                                                                       
>            .092446
          Comunitat Valenciana  |  -.0590152   .0535053    -1.10   0.272    -.1
> 649797                                                                       
>           .0469492
                   Extremadura  |  -.0014359   .0615402    -0.02   0.981     -.
> 123313                                                                       
>           .1204412
                       Galicia  |   -.102022   .0490824    -2.08   0.040    -.1
> 992271                                                                       
>          -.0048169
         Madrid (Comunidad de)  |   .0720807   .0585153     1.23   0.220    -.0
> 438058                                                                       
>           .1879673
            Murcia (Región de)  |   -.067926   .0409147    -1.66   0.100    -.1
> 489554                                                                       
>           .0131034
  Navarra (Comunidad Foral de)  |   -.019749    .051023    -0.39   0.699    -.1
> 207974                                                                       
>           .0812994
                    País Vasco  |  -.0714044   .0524778    -1.36   0.176     -.
> 175334                                                                       
>           .0325251
                    Rioja (La)  |   -.103385   .0458394    -2.26   0.026    -.1
> 941674                                                                       
>          -.0126025
    Ceuta (Ciudad Autónoma de)  |   .0406245    .057109     0.71   0.478     -.
> 072477                                                                       
>            .153726
  Melilla (Ciudad Autónoma de)  |  -.0004251   .0489017    -0.01   0.993    -.0
> 972724                                                                       
>           .0964223
                                |
                          _cons |   .1383354   .1203046     1.15   0.253    -.0
> 999216                                                                       
>           .3765924
-------------------------------------------------------------------------------
------------------

. est store uncomf_vox_controls

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. * Make table (without full list of controls)
. esttab uncomf_cs_nocontrols uncomf_cs_controls uncomf_vox_nocontrols uncomf_v
> ox_controls using 03_tables/tablef2.tex, tex se replace keep(cabine_use cs_du
> mmy vox_dummy cabine_use_cs cabine_use_vox) coeflabels (cabine_use "Used boot
> h to vote" cs_dummy "Ciudadanos voter" vox_dummy "Vox voter" cabine_use_cs "U
> sed booth x Cs voter" cabine_use_vox "Used booth x Vox voter") nomtitles star
> (* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")) addnotes("Standard e
> rrors are clustered by municipality" "The outcome variable is a dummy for whe
> ther each respondent showed" "signs of discomfort during the survey interview
> " "Models 2 and 4 include controls for income, education, age, age squared, s
> ize of" "respondent's municipality, and a dummy for respondents identifying a
> s female" "The analyses exclude respondents who voted for PP") scalars(e(N))
(output written to 03_tables/tablef2.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/tablef3.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Generate interaction
. gen prefdem_pp = democracy_pref * pp_dummy
(1,515 missing values generated)

. 
. * Run analyses
. regr cabine_use democracy_pref, cluster(municipality)

Linear regression                               Number of obs     =      1,803
                                                F(1, 123)         =       6.18
                                                Prob > F          =     0.0143
                                                R-squared         =     0.0067
                                                Root MSE          =     .49525

                           (Std. err. adjusted for 124 clusters in municipality
> )
-------------------------------------------------------------------------------
-
               |               Robust
    cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval
> ]
---------------+---------------------------------------------------------------
-
democracy_pref |  -.1420741   .0571493    -2.49   0.014    -.2551976   -.028950
> 6
         _cons |   .5714286   .0599532     9.53   0.000     .4527549    .690102
> 2
-------------------------------------------------------------------------------
-

. est store prefsystem_1

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr cabine_use democracy_pref female i.income age age_sq i.education  i.TAMU
> NI i.CCAA, cluster(municipality)

Linear regression                               Number of obs     =      1,328
                                                F(41, 119)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2407
                                                Root MSE          =     .44259

                                            (Std. err. adjusted for 120 cluster
> s in municipality)
-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                 democracy_pref |  -.0809353   .0475897    -1.70   0.092    -.1
> 751676                                                                       
>            .013297
                         female |  -.0087757   .0284077    -0.31   0.758    -.0
> 650258                                                                       
>           .0474744
                                |
                         income |
         Menos o igual a 300 €  |  -.0532461   .1051577    -0.51   0.614    -.2
> 614688                                                                       
>           .1549766
                De 301 a 600 €  |  -.0102763   .0619196    -0.17   0.868    -.1
> 328834                                                                       
>           .1123308
                De 601 a 900 €  |   -.044284   .0474911    -0.93   0.353    -.1
> 383212                                                                       
>           .0497531
              De 901 a 1.200 €  |  -.0602879   .0522661    -1.15   0.251    -.1
> 637799                                                                       
>           .0432042
            De 1.201 a 1.800 €  |  -.0322067   .0529135    -0.61   0.544    -.1
> 369807                                                                       
>           .0725673
            De 1.801 a 2.400 €  |   .0025171   .0587642     0.04   0.966    -.1
> 138418                                                                       
>           .1188761
            De 2.401 a 3.000 €  |  -.0368295   .0732787    -0.50   0.616    -.1
> 819286                                                                       
>           .1082696
            De 3.001 a 4.500 €  |   .1281344   .1280461     1.00   0.319    -.1
> 254097                                                                       
>           .3816785
            De 4.501 a 6.000 €  |  -.4391704   .2117059    -2.07   0.040    -.8
> 583692                                                                       
>          -.0199715
                Más de 6.000 €  |   .0334682   .2747742     0.12   0.903    -.5
> 106122                                                                       
>           .5775486
                                |
                            age |   .0006543   .0044818     0.15   0.884    -.0
> 082202                                                                       
>           .0095287
                         age_sq |  -.0000264   .0000489    -0.54   0.590    -.0
> 001233                                                                       
>           .0000704
                                |
                      education |
                      Primaria  |  -.0538417   .0954836    -0.56   0.574    -.2
> 429088                                                                       
>           .1352254
           Secundaria 1ª etapa  |  -.1168811   .1111733    -1.05   0.295    -.3
> 370154                                                                       
>           .1032531
           Secundaria 2ª etapa  |  -.1497287   .1055851    -1.42   0.159    -.3
> 587978                                                                       
>           .0593405
                          F.P.  |  -.0788242   .1081076    -0.73   0.467     -.
> 292888                                                                       
>           .1352396
                    Superiores  |  -.0862214   .1060854    -0.81   0.418    -.2
> 962811                                                                       
>           .1238384
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0211949   .0651548    -0.33   0.746     -.
> 150208                                                                       
>           .1078181
    10.001 a 50.000 habitantes  |  -.1472519   .0657773    -2.24   0.027    -.2
> 774975                                                                       
>          -.0170064
   50.001 a 100.000 habitantes  |   -.182463    .074976    -2.43   0.016    -.3
> 309231                                                                       
>           -.034003
  100.001 a 400.000 habitantes  |  -.2391053   .0681371    -3.51   0.001    -.3
> 740236                                                                       
>           -.104187
400.001 a 1.000.000 habitantes  |  -.3887333   .0693444    -5.61   0.000    -.5
> 260421                                                                       
>          -.2514245
   Más de 1.000.000 habitantes  |  -.2669588   .0701502    -3.81   0.000    -.4
> 058632                                                                       
>          -.1280543
                                |
                           CCAA |
                        Aragón  |  -.0346921   .0790938    -0.44   0.662    -.1
> 913058                                                                       
>           .1219216
      Asturias (Principado de)  |  -.2153858   .0715513    -3.01   0.003    -.3
> 570645                                                                       
>           -.073707
               Balears (Illes)  |  -.1849568     .11089    -1.67   0.098      -
> .40453                                                                       
>           .0346164
                      Canarias  |   .3520335   .0393317     8.95   0.000     .2
> 741528                                                                       
>           .4299142
                     Cantabria  |  -.0558895   .0981666    -0.57   0.570    -.2
> 502692                                                                       
>           .1384902
            Castilla-La Mancha  |   .0059038   .0721482     0.08   0.935    -.1
> 369568                                                                       
>           .1487644
               Castilla y León  |   .0441169   .0804529     0.55   0.584    -.1
> 151878                                                                       
>           .2034217
                      Cataluña  |  -.4476153   .0658107    -6.80   0.000    -.5
> 779271                                                                       
>          -.3173035
          Comunitat Valenciana  |  -.0920522   .0583235    -1.58   0.117    -.2
> 075386                                                                       
>           .0234341
                   Extremadura  |   .1571666   .0709395     2.22   0.029     .0
> 166992                                                                       
>            .297634
                       Galicia  |  -.0386624   .0740858    -0.52   0.603    -.1
> 853597                                                                       
>           .1080349
         Madrid (Comunidad de)  |  -.3842539   .0396661    -9.69   0.000    -.4
> 627967                                                                       
>           -.305711
            Murcia (Región de)  |   .1328082   .0692999     1.92   0.058    -.0
> 044126                                                                       
>            .270029
  Navarra (Comunidad Foral de)  |  -.1793654   .0647534    -2.77   0.007    -.3
> 075837                                                                       
>          -.0511471
                    País Vasco  |  -.1133751   .0667076    -1.70   0.092    -.2
> 454629                                                                       
>           .0187127
                    Rioja (La)  |  -.0575639   .0956181    -0.60   0.548    -.2
> 468974                                                                       
>           .1317695
    Ceuta (Ciudad Autónoma de)  |   .2376027    .053146     4.47   0.000     .1
> 323683                                                                       
>           .3428371
  Melilla (Ciudad Autónoma de)  |   .1402805   .0526144     2.67   0.009     .0
> 360988                                                                       
>           .2444622
                                |
                          _cons |   .9787606   .1407562     6.95   0.000     .7
> 000492                                                                       
>           1.257472
-------------------------------------------------------------------------------
------------------

. est store prefsystem_2

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. regr cabine_use democracy_pref pp_dummy prefdem_pp, cluster(municipality)

Linear regression                               Number of obs     =      1,802
                                                F(3, 123)         =       7.93
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0147
                                                Root MSE          =     .49347

                           (Std. err. adjusted for 124 clusters in municipality
> )
-------------------------------------------------------------------------------
-
               |               Robust
    cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval
> ]
---------------+---------------------------------------------------------------
-
democracy_pref |  -.1215299   .0587935    -2.07   0.041    -.2379079   -.005151
> 8
      pp_dummy |   .2738095   .0946389     2.89   0.005     .0864777    .461141
> 4
    prefdem_pp |  -.1685134   .0980463    -1.72   0.088      -.36259    .025563
> 2
         _cons |   .5357143   .0617693     8.67   0.000     .4134457    .657982
> 8
-------------------------------------------------------------------------------
-

. est store prefsystem_3

. estadd local Controls "No"

added macro:
           e(Controls) : "No"

. 
. regr cabine_use democracy_pref pp_dummy prefdem_pp female i.income age age_sq
>  i.education i.TAMUNI i.CCAA, cluster(municipality)

Linear regression                               Number of obs     =      1,327
                                                F(43, 119)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2461
                                                Root MSE          =     .44134

                                            (Std. err. adjusted for 120 cluster
> s in municipality)
-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                 democracy_pref |  -.0594136   .0519063    -1.14   0.255    -.1
> 621933                                                                       
>            .043366
                       pp_dummy |   .2321022   .0889863     2.61   0.010     .0
> 559004                                                                       
>            .408304
                     prefdem_pp |  -.1474944   .0977133    -1.51   0.134    -.3
> 409764                                                                       
>           .0459876
                         female |  -.0098223   .0285212    -0.34   0.731    -.0
> 662971                                                                       
>           .0466524
                                |
                         income |
         Menos o igual a 300 €  |  -.0529028   .1019904    -0.52   0.605    -.2
> 548539                                                                       
>           .1490483
                De 301 a 600 €  |  -.0008891   .0619713    -0.01   0.989    -.1
> 235985                                                                       
>           .1218203
                De 601 a 900 €  |  -.0369908    .047098    -0.79   0.434    -.1
> 302496                                                                       
>            .056268
              De 901 a 1.200 €  |  -.0488753   .0517198    -0.95   0.347    -.1
> 512857                                                                       
>           .0535352
            De 1.201 a 1.800 €  |  -.0201109   .0520246    -0.39   0.700    -.1
> 231249                                                                       
>           .0829031
            De 1.801 a 2.400 €  |   .0109765    .059107     0.19   0.853    -.1
> 060612                                                                       
>           .1280142
            De 2.401 a 3.000 €  |  -.0355474    .074478    -0.48   0.634    -.1
> 830213                                                                       
>           .1119266
            De 3.001 a 4.500 €  |   .1398819   .1282075     1.09   0.277    -.1
> 139817                                                                       
>           .3937456
            De 4.501 a 6.000 €  |   -.423323   .2055271    -2.06   0.042    -.8
> 302871                                                                       
>          -.0163589
                Más de 6.000 €  |   .0424863   .2914875     0.15   0.884    -.5
> 346881                                                                       
>           .6196606
                                |
                            age |   .0001536   .0044163     0.03   0.972    -.0
> 085912                                                                       
>           .0088984
                         age_sq |  -.0000243   .0000484    -0.50   0.616    -.0
> 001202                                                                       
>           .0000716
                                |
                      education |
                      Primaria  |  -.0719673   .0971868    -0.74   0.460     -.
> 264407                                                                       
>           .1204723
           Secundaria 1ª etapa  |  -.1291629   .1132308    -1.14   0.256    -.3
> 533712                                                                       
>           .0950453
           Secundaria 2ª etapa  |   -.164344   .1067944    -1.54   0.126    -.3
> 758075                                                                       
>           .0471195
                          F.P.  |  -.0932923   .1100557    -0.85   0.398    -.3
> 112137                                                                       
>            .124629
                    Superiores  |  -.1019192   .1090237    -0.93   0.352    -.3
> 177971                                                                       
>           .1139587
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0144295   .0640876    -0.23   0.822    -.1
> 413294                                                                       
>           .1124705
    10.001 a 50.000 habitantes  |  -.1384292   .0650732    -2.13   0.035    -.2
> 672806                                                                       
>          -.0095779
   50.001 a 100.000 habitantes  |  -.1784314   .0746398    -2.39   0.018    -.3
> 262256                                                                       
>          -.0306372
  100.001 a 400.000 habitantes  |  -.2294786   .0671618    -3.42   0.001    -.3
> 624656                                                                       
>          -.0964916
400.001 a 1.000.000 habitantes  |  -.3823549   .0683166    -5.60   0.000    -.5
> 176286                                                                       
>          -.2470812
   Más de 1.000.000 habitantes  |  -.2629658   .0685886    -3.83   0.000     -.
> 398778                                                                       
>          -.1271535
                                |
                           CCAA |
                        Aragón  |  -.0210239    .079933    -0.26   0.793    -.1
> 792992                                                                       
>           .1372515
      Asturias (Principado de)  |  -.2060275   .0724161    -2.85   0.005    -.3
> 494187                                                                       
>          -.0626363
               Balears (Illes)  |  -.1783473   .1143569    -1.56   0.122    -.4
> 047854                                                                       
>           .0480908
                      Canarias  |   .3604295   .0404877     8.90   0.000     .2
> 802599                                                                       
>           .4405991
                     Cantabria  |  -.0548109   .0996341    -0.55   0.583    -.2
> 520964                                                                       
>           .1424746
            Castilla-La Mancha  |   .0017948   .0691638     0.03   0.979    -.1
> 351564                                                                       
>           .1387461
               Castilla y León  |   .0414657   .0750585     0.55   0.582    -.1
> 071576                                                                       
>            .190089
                      Cataluña  |   -.434377   .0643159    -6.75   0.000     -.
> 561729                                                                       
>           -.307025
          Comunitat Valenciana  |  -.0898797    .058549    -1.54   0.127    -.2
> 058126                                                                       
>           .0260532
                   Extremadura  |   .1564765   .0739621     2.12   0.036     .0
> 100242                                                                       
>           .3029288
                       Galicia  |  -.0297579   .0745729    -0.40   0.691    -.1
> 774197                                                                       
>           .1179039
         Madrid (Comunidad de)  |  -.3830771   .0393255    -9.74   0.000    -.4
> 609456                                                                       
>          -.3052086
            Murcia (Región de)  |   .1298451   .0660844     1.96   0.052    -.0
> 010087                                                                       
>           .2606989
  Navarra (Comunidad Foral de)  |  -.1662507   .0691477    -2.40   0.018      -
> .30317                                                                       
>          -.0293314
                    País Vasco  |  -.1124704   .0750475    -1.50   0.137     -.
> 261072                                                                       
>           .0361311
                    Rioja (La)  |  -.0696765   .0980467    -0.71   0.479    -.2
> 638188                                                                       
>           .1244658
    Ceuta (Ciudad Autónoma de)  |   .2388749   .0546371     4.37   0.000      .
> 130688                                                                       
>           .3470619
  Melilla (Ciudad Autónoma de)  |   .1254754   .0530642     2.36   0.020      .
> 020403                                                                       
>           .2305479
                                |
                          _cons |   .9606181    .142187     6.76   0.000     .6
> 790736                                                                       
>           1.242163
-------------------------------------------------------------------------------
------------------

. est store prefsystem_4

. estadd local Controls "Yes"

added macro:
           e(Controls) : "Yes"

. 
. * Make table
. esttab prefsystem_1 prefsystem_2 prefsystem_3 prefsystem_4 using 03_tables/ta
> blef3.tex, tex se replace  keep (democracy_pref pp_dummy prefdem_pp) coeflabe
> ls (democracy_pref "Prefers democracy" pp_dummy "PP voter" prefdem_pp "Prefer
>  dem x PP voter") star(* 0.10 ** 0.05 *** 0.01) s(Controls, label("Controls")
> ) nomtitles addnotes("Standard errors are clustered by municipality" "The out
> come variable is a dummy for whether each respondent used a private" "voting 
> booth to cast their vote in the general election of November 2019" "Models 2 
> and 4 include controls for income, education, age, age squared, size of" "res
> pondent's municipality, and a dummy for respondents identifying as female")
(output written to 03_tables/tablef3.tex)

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured1_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. use 01_data/whole_spain.dta, clear

. 
. * Fake model to get the dataset started
. reg pp_voteshare turnout 

      Source |       SS           df       MS      Number of obs   =   225,903
-------------+----------------------------------   F(1, 225901)    =    485.86
       Model |  153061.286         1  153061.286   Prob > F        =    0.0000
    Residual |  71165552.8   225,901  315.029826   R-squared       =    0.0021
-------------+----------------------------------   Adj R-squared   =    0.0021
       Total |  71318614.1   225,902  315.705988   Root MSE        =    17.749

------------------------------------------------------------------------------
pp_voteshare | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     turnout |   .0629035   .0028538    22.04   0.000     .0573102    .0684968
       _cons |   26.25163   .1646255   159.46   0.000     25.92897     26.5743
------------------------------------------------------------------------------

. regsave turnout using 01_data/other_outcomes.dta, ci replace addlabel (Outcom
> e, fake, Model, 0) 
file 01_data/other_outcomes.dta saved

. 
. * Turnout
. reghdfe turnout post##ep##ciutadella if period > 1, absorb(mesa_code_elecspec
> ific) cluster(mesa_code_elecspecific)
(dropped 31824 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,458
Absorbing 1 HDFE group                            F(   4,  57728) =   62304.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9274
                                                  Adj R-squared   =     0.8548
                                                  Within R-sq.    =     0.8395
Number of clusters (mesa_code_elecspecific) =     57,729Root MSE  =     4.8480

                  (Std. err. adjusted for 57,729 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
           turnout | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -.1599082   .0371974    -4.30   0.000    -.2328153   -.08
> 70011
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   19.05648   .0531147   358.78   0.000     18.95238    19.
> 16059
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   2.329691   .3869431     6.02   0.000      1.57128    3.0
> 88101
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.173203   .7900031    -2.75   0.006    -3.721613   -.62
> 47929
                   |
             _cons |   52.31787   .0142676  3666.90   0.000      52.2899    52.
> 34583
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57729       57729           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Turnout, Model, Model 1)
(note: variable Model was byte in the using data, but will be str7 now)
file 01_data/other_outcomes.dta saved

. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella if period > 1, absorb(mesa_code_e
> lecspecific) cluster(mesa_code_elecspecific)
(dropped 34983 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    102,210
Absorbing 1 HDFE group                            F(   4,  51104) =   16593.72
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9198
                                                  Adj R-squared   =     0.8397
                                                  Within R-sq.    =     0.5661
Number of clusters (mesa_code_elecspecific) =     51,105Root MSE  =     5.4079

                  (Std. err. adjusted for 51,105 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
    psoe_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   6.320677   .0588928   107.33   0.000     6.205246    6.4
> 36107
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    3.36237   .0719795    46.71   0.000     3.221289     3.
> 50345
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -4.521106   .4829701    -9.36   0.000    -5.467733    -3.
> 57448
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   1.550474   .8375237     1.85   0.064    -.0910815    3.1
> 92029
                   |
             _cons |   24.18194   .0169151  1429.60   0.000     24.14879     24
> .2151
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     51105       51105           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, PSOE voteshare, Model, Model 1)
file 01_data/other_outcomes.dta saved

. 
. * Null votes
. reghdfe null_share post##ep##ciutadella if period > 1, absorb(mesa_code_elecs
> pecific) cluster(mesa_code_elecspecific)
(dropped 31793 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,514
Absorbing 1 HDFE group                            F(   4,  57756) =    4971.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6719
                                                  Adj R-squared   =     0.3437
                                                  Within R-sq.    =     0.2502
Number of clusters (mesa_code_elecspecific) =     57,757Root MSE  =     1.0769

                  (Std. err. adjusted for 57,757 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
        null_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   -.492655   .0060073   -82.01   0.000    -.5044294   -.48
> 08806
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.5141124   .0106547   -48.25   0.000    -.5349956   -.49
> 32291
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.5073597   .1437086    -3.53   0.000    -.7890293   -.22
> 56901
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   .5641325   .2447356     2.31   0.021     .0844495    1.0
> 43816
                   |
             _cons |   1.620018   .0031685   511.28   0.000     1.613808    1.6
> 26229
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57757       57757           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Null votes, Model, Model 1)
(variable Outcome was str10, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * White votes
. reghdfe white_share post##ep##ciutadella if period > 1, absorb(mesa_code_elec
> specific) cluster(mesa_code_elecspecific)
(dropped 31793 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,514
Absorbing 1 HDFE group                            F(   4,  57756) =    4972.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6720
                                                  Adj R-squared   =     0.3440
                                                  Within R-sq.    =     0.2503
Number of clusters (mesa_code_elecspecific) =     57,757Root MSE  =     1.0770

                  (Std. err. adjusted for 57,757 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
       white_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   -.492655   .0060073   -82.01   0.000    -.5044294   -.48
> 08806
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.5141124   .0106547   -48.25   0.000    -.5349956   -.49
> 32291
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -1.130555    .218341    -5.18   0.000    -1.558505   -.70
> 26058
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   1.141717   .3217916     3.55   0.000     .5110037     1.
> 77243
                   |
             _cons |   1.620994   .0031689   511.52   0.000     1.614783    1.6
> 27205
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57757       57757           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, White votes, Model, Model 1)
(variable Outcome was str11, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * Turnout
. reghdfe turnout post##ep##ciutadella, absorb(mesa_code_elecspecific) cluster(
> mesa_code_elecspecific)
(dropped 26175 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,025
Absorbing 1 HDFE group                            F(   4,  74345) =   84621.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9010
                                                  Adj R-squared   =     0.8424
                                                  Within R-sq.    =     0.7671
Number of clusters (mesa_code_elecspecific) =     74,346Root MSE  =     5.1743

                  (Std. err. adjusted for 74,346 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
           turnout | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -.0116717   .0404552    -0.29   0.773    -.0909638    .06
> 76204
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   18.63451   .0516189   361.00   0.000     18.53333    18.
> 73568
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.1282287   .4232328    -0.30   0.762    -.9577632    .70
> 13059
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   1.110535   .7304916     1.52   0.128    -.3212255    2.5
> 42295
                   |
             _cons |   51.61344   .0091663  5630.81   0.000     51.59547     51
> .6314
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74346       74346           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Turnout, Model, Model 2)
(variable Outcome was str7, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella, absorb(mesa_code_elecspecific) c
> luster(mesa_code_elecspecific)
(dropped 27044 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    188,048
Absorbing 1 HDFE group                            F(   4,  71382) =    1793.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7743
                                                  Adj R-squared   =     0.6361
                                                  Within R-sq.    =     0.0357
Number of clusters (mesa_code_elecspecific) =     71,383Root MSE  =     8.6859

                  (Std. err. adjusted for 71,383 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
    psoe_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   4.524834   .0669329    67.60   0.000     4.393646    4.6
> 56022
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -2.644063   .0764808   -34.57   0.000    -2.793965   -2.4
> 94161
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -4.650142   .4871586    -9.55   0.000    -5.604972   -3.6
> 95313
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -.1374131   .8278103    -0.17   0.868    -1.759919    1.4
> 85093
                   |
             _cons |   29.98934   .0108453  2765.20   0.000     29.96808    30.
> 01059
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     71383       71383           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, PSOE voteshare, Model, Model 2)
file 01_data/other_outcomes.dta saved

. 
. * Null votes
. reghdfe null_share post##ep##ciutadella, absorb(mesa_code_elecspecific) clust
> er(mesa_code_elecspecific)
(dropped 26129 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,146
Absorbing 1 HDFE group                            F(   4,  74390) =    5487.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4248
                                                  Adj R-squared   =     0.0845
                                                  Within R-sq.    =     0.0555
Number of clusters (mesa_code_elecspecific) =     74,391Root MSE  =     1.1732

                  (Std. err. adjusted for 74,391 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
        null_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   -.781051   .0056193  -138.99   0.000    -.7920649   -.77
> 00372
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4838434    .008123    59.56   0.000     .4679223    .49
> 97644
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.1693498   .1265599    -1.34   0.181    -.4174067    .07
> 87072
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   .0744123   .2131055     0.35   0.727    -.3432737    .49
> 20983
                   |
             _cons |   1.226293   .0016157   758.97   0.000     1.223126     1.
> 22946
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74391       74391           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Null votes, Model, Model 2)
(variable Outcome was str10, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * White votes
. reghdfe white_share post##ep##ciutadella, absorb(mesa_code_elecspecific) clus
> ter(mesa_code_elecspecific)
(dropped 26129 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,146
Absorbing 1 HDFE group                            F(   4,  74390) =    5496.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4255
                                                  Adj R-squared   =     0.0856
                                                  Within R-sq.    =     0.0558
Number of clusters (mesa_code_elecspecific) =     74,391Root MSE  =     1.1733

                  (Std. err. adjusted for 74,391 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
       white_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |   -.781051   .0056193  -138.99   0.000    -.7920649   -.77
> 00372
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4838434    .008123    59.56   0.000     .4679223    .49
> 97644
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -1.081618    .206961    -5.23   0.000    -1.487261   -.67
> 59758
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   .4291695   .2991733     1.43   0.151     -.157209    1.0
> 15548
                   |
             _cons |   1.227474    .001616   759.57   0.000     1.224307    1.2
> 30642
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74391       74391           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, White votes, Model, Model 2)
(variable Outcome was str11, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * Turnout
. reghdfe turnout post##ep##ciutadella i.period, absorb(mesa_code_elecspecific)
>  cluster(mesa_code_elecspecific)
(dropped 26175 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,025
Absorbing 1 HDFE group                            F(   5,  74345) =   68837.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9011
                                                  Adj R-squared   =     0.8425
                                                  Within R-sq.    =     0.7672
Number of clusters (mesa_code_elecspecific) =     74,346Root MSE  =     5.1730

                  (Std. err. adjusted for 74,346 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
           turnout | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -.1344273   .0453118    -2.97   0.003    -.2232382   -.04
> 56163
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   18.65512   .0518217   359.99   0.000     18.55355    18.
> 75669
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.1221533   .4232434    -0.29   0.773    -.9517086    .70
> 74021
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   1.089922   .7305003     1.49   0.136    -.3418561    2.5
> 21699
                   |
            period |
                2  |  -.2333604    .028256    -8.26   0.000    -.2887421   -.17
> 79787
                3  |          0  (omitted)
                   |
             _cons |   51.72298   .0173612  2979.23   0.000     51.68895    51.
> 75701
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74346       74346           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Turnout, Model, Model 3)
(variable Outcome was str7, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * PSOE
. reghdfe psoe_voteshare post##ep##ciutadella i.period, absorb(mesa_code_elecsp
> ecific) cluster(mesa_code_elecspecific)
(dropped 27044 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    188,048
Absorbing 1 HDFE group                            F(   5,  71382) =   22270.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8765
                                                  Adj R-squared   =     0.8009
                                                  Within R-sq.    =     0.4723
Number of clusters (mesa_code_elecspecific) =     71,383Root MSE  =     6.4251

                  (Std. err. adjusted for 71,383 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
    psoe_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -1.606054   .0744824   -21.56   0.000     -1.75204   -1.4
> 60069
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.650374   .0756148   -21.83   0.000    -1.798579    -1.
> 50217
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -4.376381   .4871712    -8.98   0.000    -5.331235   -3.4
> 21527
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -1.131101   .8277357    -1.37   0.172    -2.753461    .49
> 12584
                   |
            period |
                2  |  -11.71425   .0397514  -294.69   0.000    -11.79217   -11.
> 63634
                3  |          0  (omitted)
                   |
             _cons |   35.51786   .0228602  1553.70   0.000     35.47306    35.
> 56267
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     71383       71383           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, PSOE voteshare, Model, Model 3)
file 01_data/other_outcomes.dta saved

. 
. * Null votes
. reghdfe null_share post##ep##ciutadella i.period, absorb(mesa_code_elecspecif
> ic) cluster(mesa_code_elecspecific)
(dropped 26129 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,146
Absorbing 1 HDFE group                            F(   5,  74390) =    6134.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4728
                                                  Adj R-squared   =     0.1609
                                                  Within R-sq.    =     0.1343
Number of clusters (mesa_code_elecspecific) =     74,391Root MSE  =     1.1231

                  (Std. err. adjusted for 74,391 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
        null_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -.4145292   .0073435   -56.45   0.000    -.4289224    -.4
> 00136
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4222644   .0083138    50.79   0.000     .4059694    .43
> 85594
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.1875046   .1265668    -1.48   0.138     -.435575    .06
> 05658
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   .1359912   .2131129     0.64   0.523    -.2817092    .55
> 36916
                   |
            period |
                2  |    .696734   .0076201    91.43   0.000     .6817986    .71
> 16694
                3  |          0  (omitted)
                   |
             _cons |    .899233   .0036685   245.12   0.000     .8920428    .90
> 64232
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74391       74391           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, Null votes, Model, Model 3)
(variable Outcome was str10, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
. * White votes
. reghdfe white_share post##ep##ciutadella i.period, absorb(mesa_code_elecspeci
> fic) cluster(mesa_code_elecspecific)
(dropped 26129 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,146
Absorbing 1 HDFE group                            F(   5,  74390) =    6139.30
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4733
                                                  Adj R-squared   =     0.1617
                                                  Within R-sq.    =     0.1344
Number of clusters (mesa_code_elecspecific) =     74,391Root MSE  =     1.1234

                  (Std. err. adjusted for 74,391 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
       white_share | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -.4149258   .0073437   -56.50   0.000    -.4293194   -.40
> 05321
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .422331   .0083137    50.80   0.000     .4060361    .43
> 86259
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -1.099754    .206965    -5.31   0.000    -1.505404   -.69
> 41031
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   .4906818    .299179     1.64   0.101    -.0957077    1.0
> 77071
                   |
            period |
                2  |   .6959802   .0076216    91.32   0.000     .6810418    .71
> 09186
                3  |          0  (omitted)
                   |
             _cons |    .900768   .0036694   245.48   0.000      .893576      .
> 90796
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74391       74391           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. regsave 1.post#1.ep#1.ciutadella using 01_data/other_outcomes.dta, ci append 
> addlabel (Outcome, White votes, Model, Model 3)
(variable Outcome was str11, now str14 to accommodate using data's values)
file 01_data/other_outcomes.dta saved

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured2_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/whole_spain.dta, clear

. 
. * Fake model to get the dataset started
. reg ep post 

      Source |       SS           df       MS      Number of obs   =   231,586
-------------+----------------------------------   F(1, 231584)    =     46.55
       Model |  9.27768029         1  9.27768029   Prob > F        =    0.0000
    Residual |  46155.9124   231,584  .199305273   R-squared       =    0.0002
-------------+----------------------------------   Adj R-squared   =    0.0002
       Total |  46165.1901   231,585  .199344474   Root MSE        =    .44644

------------------------------------------------------------------------------
          ep | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        post |    .013264   .0019441     6.82   0.000     .0094537    .0170744
       _cons |   .7204182   .0011513   625.76   0.000     .7181617    .7226746
------------------------------------------------------------------------------

. regsave post using 01_data/jackknives_ddd.dta, ci replace addlabel (Region, 0
> , Model, 0)
file 01_data/jackknives_ddd.dta saved

. 
. 
. forvalues x = 1/3 {
  2. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA != `x', 
> absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
  3. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 1)
  4.         
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA != `x', absorb(mesa_code
> _elecspecific) cluster(mesa_code_elecspecific)
  5. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 2)
  6. 
. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA != `x', absorb(
> mesa_code_elecspecific) cluster(mesa_code_elecspecific)
  7. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 3)
  8. }
(dropped 26320 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    100,962
Absorbing 1 HDFE group                            F(   4,  50480) =   10876.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9450
                                                  Adj R-squared   =     0.8900
                                                  Within R-sq.    =     0.4567
Number of clusters (mesa_code_elecspecific) =     50,481Root MSE  =     4.9539

                  (Std. err. adjusted for 50,481 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |    -6.1091   .0595068  -102.66   0.000    -6.225734   -5.9
> 92466
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.4604574   .0696828    -6.61   0.000    -.5970366   -.32
> 38783
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.155187   .6930653     1.67   0.096    -.2032285    2.5
> 13603
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.645043   1.121844    -2.36   0.018     -4.84387    -.4
> 46216
                   |
             _cons |   27.59381   .0155906  1769.90   0.000     27.56325    27.
> 62437
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     50481       50481           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(note: variable Model was byte in the using data, but will be str7 now)
file 01_data/jackknives_ddd.dta saved
(dropped 21207 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    173,515
Absorbing 1 HDFE group                            F(   4,  64174) =   41088.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8251
                                                  Adj R-squared   =     0.7224
                                                  Within R-sq.    =     0.4352
Number of clusters (mesa_code_elecspecific) =     64,175Root MSE  =     9.3849

                  (Std. err. adjusted for 64,175 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.66086   .0713213  -177.52   0.000    -12.80065   -12.
> 52107
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   -1.82577   .0817103   -22.34   0.000    -1.985922   -1.6
> 65617
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    .145158   .5897541     0.25   0.806    -1.010761    1.3
> 01077
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -1.655556   1.008673    -1.64   0.101    -3.632556    .32
> 14439
                   |
             _cons |   34.71174   .0122634  2830.51   0.000      34.6877    34.
> 73577
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     64175       64175           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 21207 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    173,515
Absorbing 1 HDFE group                            F(   5,  64174) =   45322.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9174
                                                  Adj R-squared   =     0.8689
                                                  Within R-sq.    =     0.7333
Number of clusters (mesa_code_elecspecific) =     64,175Root MSE  =     6.4494

                  (Std. err. adjusted for 64,175 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -19.99006    .078737  -253.88   0.000    -20.14438   -19.
> 83574
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.6709924   .0790713    -8.49   0.000    -.8259723   -.51
> 60125
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    .497304   .5895679     0.84   0.399    -.6582496    1.6
> 52858
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.810333    1.00847    -2.79   0.005    -4.786936   -.83
> 37302
                   |
            period |
                2  |   -13.9541   .0397543  -351.01   0.000    -14.03202   -13.
> 87618
                3  |          0  (omitted)
                   |
             _cons |   41.31711   .0260045  1588.84   0.000     41.26614    41.
> 36808
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     64175       64175           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30896 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    113,892
Absorbing 1 HDFE group                            F(   4,  56945) =   10146.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9375
                                                  Adj R-squared   =     0.8749
                                                  Within R-sq.    =     0.4019
Number of clusters (mesa_code_elecspecific) =     56,946Root MSE  =     5.2475

                  (Std. err. adjusted for 56,946 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.205263   .0658088   -94.29   0.000    -6.334249   -6.0
> 76277
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1801643   .0740343     2.43   0.015     .0350566     .3
> 25272
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    1.25135   .6936325     1.80   0.071     -.108174    2.6
> 10873
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.285665   1.122119    -2.93   0.003    -5.485024   -1.0
> 86305
                   |
             _cons |    27.3271   .0155489  1757.50   0.000     27.29663    27.
> 35758
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     56946       56946           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25212 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,861
Absorbing 1 HDFE group                            F(   4,  73103) =   42819.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8197
                                                  Adj R-squared   =     0.7132
                                                  Within R-sq.    =     0.4200
Number of clusters (mesa_code_elecspecific) =     73,104Root MSE  =     9.4969

                  (Std. err. adjusted for 73,104 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.04172   .0717777  -181.70   0.000    -13.18241   -12.
> 90104
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.8898019   .0810207   -10.98   0.000    -1.048602   -.73
> 10016
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .5260166   .5898081     0.89   0.372    -.6300052    1.6
> 82038
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.591523   1.008615    -2.57   0.010    -4.568405   -.61
> 46418
                   |
             _cons |   34.54046   .0118173  2922.87   0.000      34.5173    34.
> 56362
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     73104       73104           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25212 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,861
Absorbing 1 HDFE group                            F(   5,  73103) =   49566.31
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9145
                                                  Adj R-squared   =     0.8639
                                                  Within R-sq.    =     0.7249
Number of clusters (mesa_code_elecspecific) =     73,104Root MSE  =     6.5409

                  (Std. err. adjusted for 73,104 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.47706   .0770446  -265.78   0.000    -20.62807   -20.
> 32606
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .3218699   .0782338     4.11   0.000      .168532    .47
> 52078
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .9006817    .589596     1.53   0.127    -.2549245    2.0
> 56288
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.803195   1.008402    -3.77   0.000    -5.779659   -1.8
> 26731
                   |
            period |
                2  |  -14.12135   .0374732  -376.84   0.000     -14.1948   -14.
> 04791
                3  |          0  (omitted)
                   |
             _cons |   41.20138   .0243002  1695.52   0.000     41.15375    41.
> 24901
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     73104       73104           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 31275 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,170
Absorbing 1 HDFE group                            F(   4,  57584) =   10346.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9372
                                                  Adj R-squared   =     0.8744
                                                  Within R-sq.    =     0.4052
Number of clusters (mesa_code_elecspecific) =     57,585Root MSE  =     5.2573

                  (Std. err. adjusted for 57,585 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.198538   .0646584   -95.87   0.000    -6.325268   -6.0
> 71807
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .091051    .073104     1.25   0.213    -.0522333    .23
> 43353
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.244624   .6935241     1.79   0.073    -.1146864    2.6
> 03935
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.196551   1.122058    -2.85   0.004    -5.395791   -.99
> 73123
                   |
             _cons |   27.54834   .0154914  1778.30   0.000     27.51798    27.
> 57871
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57585       57585           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25589 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    199,190
Absorbing 1 HDFE group                            F(   4,  74003) =   43664.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8210
                                                  Adj R-squared   =     0.7152
                                                  Within R-sq.    =     0.4235
Number of clusters (mesa_code_elecspecific) =     74,004Root MSE  =     9.4467

                  (Std. err. adjusted for 74,004 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.17008   .0699255  -188.34   0.000    -13.30713   -13.
> 03302
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.7360907   .0792931    -9.28   0.000    -.8915048   -.58
> 06766
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .6543699   .5895855     1.11   0.267    -.5012153    1.8
> 09955
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.745235   1.008477    -2.72   0.006    -4.721846    -.7
> 68623
                   |
             _cons |   34.72445   .0116998  2967.94   0.000     34.70151    34.
> 74738
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74004       74004           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25589 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    199,190
Absorbing 1 HDFE group                            F(   5,  74003) =   50607.88
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9152
                                                  Adj R-squared   =     0.8650
                                                  Within R-sq.    =     0.7268
Number of clusters (mesa_code_elecspecific) =     74,004Root MSE  =     6.5033

                  (Std. err. adjusted for 74,004 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.57534   .0748436  -274.91   0.000    -20.72204   -20.
> 42865
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4847417   .0764415     6.34   0.000     .3349167    .63
> 45668
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.027387   .5893718     1.74   0.081    -.1277797    2.1
> 82553
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.966067   1.008264    -3.93   0.000    -5.942261   -1.9
> 89873
                   |
            period |
                2  |   -14.0645   .0370377  -379.74   0.000    -14.13709   -13.
> 99191
                3  |          0  (omitted)
                   |
             _cons |    41.3506    .023923  1728.49   0.000     41.30372    41.
> 39749
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74004       74004           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved

. 
. * CCAA code 4 is Balearic Islands, which is why I don't remove it
. 
. forvalues x = 5/19 {
  2. reghdfe pp_voteshare post##ep##ciutadella if period > 1 & CODCCAA != `x', 
> absorb(mesa_code_elecspecific) cluster(mesa_code_elecspecific)
  3. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 1)
  4.         
. reghdfe pp_voteshare post##ep##ciutadella if CODCCAA != `x', absorb(mesa_code
> _elecspecific) cluster(mesa_code_elecspecific)
  5. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 2)
  6. 
. reghdfe pp_voteshare post##ep##ciutadella i.period if CODCCAA != `x', absorb(
> mesa_code_elecspecific) cluster(mesa_code_elecspecific)
  7. regsave 1.post#1.ep#1.ciutadella using 01_data/jackknives_ddd.dta, ci appe
> nd addlabel (Region, `x', Model, Model 3)
  8. }
(dropped 30179 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    113,994
Absorbing 1 HDFE group                            F(   4,  56996) =    9964.58
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9378
                                                  Adj R-squared   =     0.8756
                                                  Within R-sq.    =     0.3975
Number of clusters (mesa_code_elecspecific) =     56,997Root MSE  =     5.2603

                  (Std. err. adjusted for 56,997 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.075802   .0651298   -93.29   0.000    -6.203457   -5.9
> 48147
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0501689   .0735687     0.68   0.495    -.0940261    .19
> 43639
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.121889   .6935684     1.62   0.106    -.2375093    2.4
> 81287
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.155669   1.122088    -2.81   0.005    -5.354969   -.95
> 63696
                   |
             _cons |   27.58017   .0155798  1770.25   0.000     27.54963    27.
> 61071
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     56997       56997           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25107 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,192
Absorbing 1 HDFE group                            F(   4,  72789) =   42737.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8238
                                                  Adj R-squared   =     0.7198
                                                  Within R-sq.    =     0.4178
Number of clusters (mesa_code_elecspecific) =     72,790Root MSE  =     9.3963

                  (Std. err. adjusted for 72,790 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.89719   .0712886  -180.92   0.000    -13.03692   -12.
> 75747
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.8087133   .0803086   -10.07   0.000    -.9661179   -.65
> 13088
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .3814844   .5897488     0.65   0.518    -.7744213     1.
> 53739
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.672612   1.008558    -2.65   0.008    -4.649382   -.69
> 58418
                   |
             _cons |   34.66894   .0116813  2967.91   0.000     34.64605    34.
> 69184
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72790       72790           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25107 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,192
Absorbing 1 HDFE group                            F(   5,  72789) =   49337.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9159
                                                  Adj R-squared   =     0.8662
                                                  Within R-sq.    =     0.7220
Number of clusters (mesa_code_elecspecific) =     72,790Root MSE  =     6.4928

                  (Std. err. adjusted for 72,790 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.24581   .0766055  -264.29   0.000    -20.39596   -20.
> 09567
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .3727477   .0776273     4.80   0.000     .2205984    .52
> 48969
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7652598    .589536     1.30   0.194    -.3902287    1.9
> 20748
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.854073   1.008355    -3.82   0.000    -5.830446     -1
> .8777
                   |
            period |
                2  |  -13.92969   .0374091  -372.36   0.000    -14.00301   -13.
> 85637
                3  |          0  (omitted)
                   |
             _cons |    41.2619   .0241686  1707.25   0.000     41.21453    41.
> 30927
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72790       72790           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 31874 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    116,840
Absorbing 1 HDFE group                            F(   4,  58419) =   10330.90
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9371
                                                  Adj R-squared   =     0.8743
                                                  Within R-sq.    =     0.4018
Number of clusters (mesa_code_elecspecific) =     58,420Root MSE  =     5.2429

                  (Std. err. adjusted for 58,420 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.129319   .0634362   -96.62   0.000    -6.253655   -6.0
> 04984
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .078493   .0719276     1.09   0.275    -.0624854    .21
> 94714
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.175406    .693411     1.70   0.090    -.1836826    2.5
> 34495
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.183993   1.121981    -2.84   0.005    -5.383082   -.98
> 49048
                   |
             _cons |   27.31333   .0153381  1780.75   0.000     27.28327     27
> .3434
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     58420       58420           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26049 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    202,381
Absorbing 1 HDFE group                            F(   4,  75232) =   44060.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8199
                                                  Adj R-squared   =     0.7134
                                                  Within R-sq.    =     0.4223
Number of clusters (mesa_code_elecspecific) =     75,233Root MSE  =     9.4386

                  (Std. err. adjusted for 75,233 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.93163   .0693481  -186.47   0.000    -13.06755   -12.
> 79571
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.9966927    .078668   -12.67   0.000    -1.150882   -.84
> 25039
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4159221   .5895171     0.71   0.480    -.7395287    1.5
> 71373
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.484633   1.008428    -2.46   0.014    -4.461147   -.50
> 81179
                   |
             _cons |   34.49516   .0116312  2965.74   0.000     34.47237    34.
> 51796
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75233       75233           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26049 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    202,381
Absorbing 1 HDFE group                            F(   5,  75232) =   51018.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9142
                                                  Adj R-squared   =     0.8634
                                                  Within R-sq.    =     0.7247
Number of clusters (mesa_code_elecspecific) =     75,233Root MSE  =     6.5159

                  (Std. err. adjusted for 75,233 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.32252   .0745873  -272.47   0.000    -20.46871   -20.
> 17633
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2497783   .0758983     3.29   0.001      .101018    .39
> 85387
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7953691   .5893154     1.35   0.177    -.3596865    1.9
> 50425
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.731104   1.008223    -3.70   0.000    -5.707216   -1.7
> 54991
                   |
            period |
                2  |  -14.02289   .0369174  -379.85   0.000    -14.09525   -13.
> 95053
                3  |          0  (omitted)
                   |
             _cons |   41.09276   .0238375  1723.87   0.000     41.04604    41.
> 13949
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75233       75233           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30573 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    113,278
Absorbing 1 HDFE group                            F(   4,  56638) =    9822.60
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9377
                                                  Adj R-squared   =     0.8754
                                                  Within R-sq.    =     0.3959
Number of clusters (mesa_code_elecspecific) =     56,639Root MSE  =     5.1952

                  (Std. err. adjusted for 56,639 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.122634   .0643905   -95.09   0.000     -6.24884   -5.9
> 96429
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2605497   .0727136     3.58   0.000     .1180306    .40
> 30687
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.168721   .6934995     1.69   0.092    -.1905418    2.5
> 27984
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -3.36605   1.122033    -3.00   0.003    -5.565241   -1.1
> 66859
                   |
             _cons |   26.94337   .0154358  1745.51   0.000     26.91311    26.
> 97362
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     56639       56639           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25059 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    195,621
Absorbing 1 HDFE group                            F(   4,  72632) =   42114.12
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8186
                                                  Adj R-squared   =     0.7115
                                                  Within R-sq.    =     0.4156
Number of clusters (mesa_code_elecspecific) =     72,633Root MSE  =     9.4601

                  (Std. err. adjusted for 72,633 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.94376    .070527  -183.53   0.000    -13.08199   -12.
> 80552
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.7922615   .0798925    -9.92   0.000    -.9488505   -.63
> 56725
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4280502   .5896573     0.73   0.468    -.7276761    1.5
> 83777
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.689064   1.008525    -2.67   0.008    -4.665769   -.71
> 23582
                   |
             _cons |   34.11152   .0117636  2899.76   0.000     34.08847    34.
> 13458
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72633       72633           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25059 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    195,621
Absorbing 1 HDFE group                            F(   5,  72632) =   48863.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9144
                                                  Adj R-squared   =     0.8639
                                                  Within R-sq.    =     0.7243
Number of clusters (mesa_code_elecspecific) =     72,633Root MSE  =     6.4983

                  (Std. err. adjusted for 72,633 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.36634   .0759138  -268.28   0.000    -20.51513   -20.
> 21755
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4180929   .0771162     5.42   0.000     .2669453    .56
> 92404
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .8009261   .5894506     1.36   0.174    -.3543952    1.9
> 56247
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.899418   1.008316    -3.87   0.000    -5.875714   -1.9
> 23122
                   |
            period |
                2  |  -14.09942   .0373639  -377.35   0.000    -14.17265   -14.
> 02618
                3  |          0  (omitted)
                   |
             _cons |   40.76774   .0242819  1678.93   0.000     40.72015    40.
> 81533
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72633       72633           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30065 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    108,968
Absorbing 1 HDFE group                            F(   4,  54483) =    9836.08
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9342
                                                  Adj R-squared   =     0.8684
                                                  Within R-sq.    =     0.4010
Number of clusters (mesa_code_elecspecific) =     54,484Root MSE  =     5.1382

                  (Std. err. adjusted for 54,484 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.194908   .0664529   -93.22   0.000    -6.325156    -6.
> 06466
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .3737413   .0743393     5.03   0.000     .2280358    .51
> 94468
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.240995   .6936947     1.79   0.074    -.1186521    2.6
> 00642
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.479242   1.122141    -3.10   0.002    -5.678646   -1.2
> 79838
                   |
             _cons |   26.20093   .0155653  1683.29   0.000     26.17042    26.
> 23143
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     54484       54484           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24230 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    189,131
Absorbing 1 HDFE group                            F(   4,  70339) =   42122.85
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8128
                                                  Adj R-squared   =     0.7019
                                                  Within R-sq.    =     0.4236
Number of clusters (mesa_code_elecspecific) =     70,340Root MSE  =     9.4372

                  (Std. err. adjusted for 70,340 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.30853    .070078  -189.91   0.000    -13.44589   -13.
> 17118
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.5347051   .0797952    -6.70   0.000    -.6911036   -.37
> 83066
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7928266   .5896041     1.34   0.179     -.362796    1.9
> 48449
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -2.94662   1.008518    -2.92   0.003    -4.923313   -.96
> 99275
                   |
             _cons |   33.60208   .0118927  2825.43   0.000     33.57877    33.
> 62539
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     70340       70340           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24230 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    189,131
Absorbing 1 HDFE group                            F(   5,  70339) =   50612.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9157
                                                  Adj R-squared   =     0.8657
                                                  Within R-sq.    =     0.7404
Number of clusters (mesa_code_elecspecific) =     70,340Root MSE  =     6.3339

                  (Std. err. adjusted for 70,340 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |    -20.864    .073893  -282.35   0.000    -21.00883   -20.
> 71917
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .7437423   .0765023     9.72   0.000      .593798    .89
> 36867
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.165328    .589373     1.98   0.048      .010158    2.3
> 20497
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -4.225068    1.00827    -4.19   0.000    -6.201275    -2.
> 24886
                   |
            period |
                2  |  -14.36592   .0363649  -395.05   0.000     -14.4372   -14.
> 29465
                3  |          0  (omitted)
                   |
             _cons |   40.35107   .0237533  1698.76   0.000     40.30451    40.
> 39763
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     70340       70340           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 27897 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    102,038
Absorbing 1 HDFE group                            F(   4,  51018) =    8941.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9216
                                                  Adj R-squared   =     0.8433
                                                  Within R-sq.    =     0.4020
Number of clusters (mesa_code_elecspecific) =     51,019Root MSE  =     5.5300

                  (Std. err. adjusted for 51,019 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.578984   .0706424   -93.13   0.000    -6.717444   -6.4
> 40524
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2485705   .0804789     3.09   0.002     .0908311    .40
> 63099
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    1.62507   .6941099     2.34   0.019     .2646078    2.9
> 85533
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.354071   1.122566    -2.99   0.003    -5.554312    -1.
> 15383
                   |
             _cons |   30.27065   .0173117  1748.56   0.000     30.23672    30.
> 30459
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     51019       51019           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 23052 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    176,672
Absorbing 1 HDFE group                            F(   4,  65702) =   41704.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7846
                                                  Adj R-squared   =     0.6571
                                                  Within R-sq.    =     0.4312
Number of clusters (mesa_code_elecspecific) =     65,703Root MSE  =     9.8688

                  (Std. err. adjusted for 65,703 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.90367   .0744347  -186.79   0.000    -14.04956   -13.
> 75778
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.8759918   .0848933   -10.32   0.000    -1.042383    -.7
> 09601
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.387963   .5901385     2.35   0.019     .2312913    2.5
> 44634
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.605334   1.008935    -2.58   0.010    -4.582847   -.62
> 78203
                   |
             _cons |   37.93869    .012708  2985.42   0.000     37.91379     37
> .9636
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     65703       65703           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 23052 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    176,672
Absorbing 1 HDFE group                            F(   5,  65702) =   51220.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9037
                                                  Adj R-squared   =     0.8467
                                                  Within R-sq.    =     0.7458
Number of clusters (mesa_code_elecspecific) =     65,703Root MSE  =     6.5981

                  (Std. err. adjusted for 65,703 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -21.83119   .0791072  -275.97   0.000    -21.98624   -21.
> 67614
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4393754   .0813613     5.40   0.000     .2799072    .59
> 88437
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.776704   .5898578     3.01   0.003     .6205822    2.9
> 32825
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.920701   1.008652    -3.89   0.000    -5.897659   -1.9
> 43742
                   |
            period |
                2  |  -15.07756   .0400996  -376.00   0.000    -15.15615   -14.
> 99896
                3  |          0  (omitted)
                   |
             _cons |   45.03432   .0253901  1773.70   0.000     44.98456    45.
> 08409
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     65703       65703           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 31667 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,588
Absorbing 1 HDFE group                            F(   4,  57793) =   10104.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9384
                                                  Adj R-squared   =     0.8768
                                                  Within R-sq.    =     0.3993
Number of clusters (mesa_code_elecspecific) =     57,794Root MSE  =     5.1939

                  (Std. err. adjusted for 57,794 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -5.993812   .0627731   -95.48   0.000    -6.116848   -5.8
> 70777
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .008874   .0713429     0.12   0.901    -.1309585    .14
> 87065
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.039899   .6933508     1.50   0.134     -.319072     2.
> 39887
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.114374   1.121944    -2.78   0.006    -5.313391   -.91
> 53579
                   |
             _cons |   27.24864   .0152768  1783.66   0.000      27.2187    27.
> 27858
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57794       57794           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25693 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,353
Absorbing 1 HDFE group                            F(   4,  74450) =   43903.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8204
                                                  Adj R-squared   =     0.7142
                                                  Within R-sq.    =     0.4211
Number of clusters (mesa_code_elecspecific) =     74,451Root MSE  =     9.4435

                  (Std. err. adjusted for 74,451 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.77273   .0687475  -185.79   0.000    -12.90748   -12.
> 63799
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.185987   .0782014   -15.17   0.000    -1.339262   -1.0
> 32713
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .2570283   .5894469     0.44   0.663    -.8982851    1.4
> 12342
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.295338   1.008392    -2.28   0.023    -4.271782   -.31
> 88937
                   |
             _cons |   34.49153   .0116186  2968.65   0.000     34.46876    34.
> 51431
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74451       74451           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25693 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    200,353
Absorbing 1 HDFE group                            F(   5,  74450) =   51278.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9157
                                                  Adj R-squared   =     0.8658
                                                  Within R-sq.    =     0.7282
Number of clusters (mesa_code_elecspecific) =     74,451Root MSE  =     6.4705

                  (Std. err. adjusted for 74,451 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.20795   .0739446  -273.29   0.000    -20.35288   -20.
> 06302
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0700759   .0753547     0.93   0.352     -.077619    .21
> 77708
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .6323748   .5892412     1.07   0.283    -.5225355    1.7
> 87285
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.551401   1.008182    -3.52   0.000    -5.527435   -1.5
> 75368
                   |
            period |
                2  |  -14.11974   .0368069  -383.62   0.000    -14.19188    -14
> .0476
                3  |          0  (omitted)
                   |
             _cons |   41.13008   .0237773  1729.80   0.000     41.08347    41.
> 17668
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74451       74451           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30632 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    110,118
Absorbing 1 HDFE group                            F(   4,  55058) =   10085.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9370
                                                  Adj R-squared   =     0.8740
                                                  Within R-sq.    =     0.4110
Number of clusters (mesa_code_elecspecific) =     55,059Root MSE  =     5.1803

                  (Std. err. adjusted for 55,059 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.177738   .0640535   -96.45   0.000    -6.303283   -6.0
> 52193
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .087667   .0728209     1.20   0.229    -.0550624    .23
> 03965
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.223825   .6934688     1.76   0.078    -.1353789    2.5
> 83029
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.193167   1.122041    -2.85   0.004    -5.392375   -.99
> 39597
                   |
             _cons |   26.97958   .0156106  1728.28   0.000     26.94899    27.
> 01018
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     55059       55059           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25000 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    191,103
Absorbing 1 HDFE group                            F(   4,  71101) =   42000.74
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8202
                                                  Adj R-squared   =     0.7136
                                                  Within R-sq.    =     0.4253
Number of clusters (mesa_code_elecspecific) =     71,102Root MSE  =     9.4026

                  (Std. err. adjusted for 71,102 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.88145   .0696502  -184.94   0.000    -13.01796   -12.
> 74494
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.105568   .0795145   -13.90   0.000    -1.261417   -.94
> 97201
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .3657432   .5895533     0.62   0.535    -.7897797    1.5
> 21266
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.375757   1.008496    -2.36   0.018    -4.352406   -.39
> 91084
                   |
             _cons |    34.1425   .0119207  2864.14   0.000     34.11914    34.
> 16586
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     71102       71102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25000 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    191,103
Absorbing 1 HDFE group                            F(   5,  71101) =   48075.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9144
                                                  Adj R-squared   =     0.8637
                                                  Within R-sq.    =     0.7265
Number of clusters (mesa_code_elecspecific) =     71,102Root MSE  =     6.4862

                  (Std. err. adjusted for 71,102 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.24712   .0748427  -270.53   0.000    -20.39381   -20.
> 10043
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .149976   .0765747     1.96   0.050    -.0001102    .30
> 00621
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7386237   .5893397     1.25   0.210    -.4164806    1.8
> 93728
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.631301   1.008276    -3.60   0.000    -5.607519   -1.6
> 55084
                   |
            period |
                2  |  -13.98559   .0378008  -369.98   0.000    -14.05968    -13
> .9115
                3  |          0  (omitted)
                   |
             _cons |   40.71271   .0244486  1665.24   0.000     40.66479    40.
> 76063
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     71102       71102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25779 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    102,378
Absorbing 1 HDFE group                            F(   4,  51188) =    7750.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9380
                                                  Adj R-squared   =     0.8759
                                                  Within R-sq.    =     0.3581
Number of clusters (mesa_code_elecspecific) =     51,189Root MSE  =     5.3362

                  (Std. err. adjusted for 51,189 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -4.910357   .0723942   -67.83   0.000     -5.05225   -4.7
> 68464
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.9997615   .0810604   -12.33   0.000    -1.158641   -.84
> 08823
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.0435562   .6942903    -0.06   0.950    -1.404372     1.
> 31726
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.105739   1.122608    -1.88   0.061    -4.306062    .09
> 45842
                   |
             _cons |   26.94944   .0166773  1615.93   0.000     26.91676    26.
> 98213
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     51189       51189           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 22427 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    175,678
Absorbing 1 HDFE group                            F(   4,  65289) =   34289.75
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8268
                                                  Adj R-squared   =     0.7244
                                                  Within R-sq.    =     0.4008
Number of clusters (mesa_code_elecspecific) =     65,290Root MSE  =     9.3631

                  (Std. err. adjusted for 65,290 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -11.38196    .078825  -144.40   0.000    -11.53646   -11.
> 22746
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -2.035027   .0881611   -23.08   0.000    -2.207823   -1.8
> 62231
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -1.133748   .5907084    -1.92   0.055    -2.291537    .02
> 40402
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -1.446298   1.009216    -1.43   0.152    -3.424361    .53
> 17646
                   |
             _cons |   33.74615   .0126178  2674.48   0.000     33.72142    33.
> 77088
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     65290       65290           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 22427 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    175,678
Absorbing 1 HDFE group                            F(   5,  65289) =   38856.06
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9116
                                                  Adj R-squared   =     0.8593
                                                  Within R-sq.    =     0.6941
Number of clusters (mesa_code_elecspecific) =     65,290Root MSE  =     6.6902

                  (Std. err. adjusted for 65,290 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -18.59848   .0855152  -217.49   0.000    -18.76609   -18.
> 43087
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.7965189   .0858714    -9.28   0.000    -.9648269    -.6
> 28211
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |  -.6597322     .59053    -1.12   0.264    -1.817171    .49
> 77069
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.684806   1.009027    -2.66   0.008    -4.662499   -.70
> 71141
                   |
            period |
                2  |  -13.48502   .0414641  -325.22   0.000    -13.56629   -13.
> 40375
                3  |          0  (omitted)
                   |
             _cons |   40.12914   .0266204  1507.46   0.000     40.07696    40.
> 18131
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     65290       65290           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 31376 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    117,264
Absorbing 1 HDFE group                            F(   4,  58631) =   10423.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4033
Number of clusters (mesa_code_elecspecific) =     58,632Root MSE  =     5.2379

                  (Std. err. adjusted for 58,632 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.121899    .062844   -97.41   0.000    -6.245074   -5.9
> 98725
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0487604   .0714108     0.68   0.495    -.0912052    .18
> 87259
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.167986    .693357     1.68   0.092    -.1909967    2.5
> 26969
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.154261   1.121948    -2.81   0.005    -5.353284   -.95
> 52372
                   |
             _cons |   27.45703   .0152959  1795.06   0.000     27.42705    27.
> 48701
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     58632       58632           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26018 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    202,042
Absorbing 1 HDFE group                            F(   4,  74968) =   44205.95
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8189
                                                  Adj R-squared   =     0.7120
                                                  Within R-sq.    =     0.4220
Number of clusters (mesa_code_elecspecific) =     74,969Root MSE  =     9.4627

                  (Std. err. adjusted for 74,969 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.92846   .0686972  -188.19   0.000     -13.0631   -12.
> 79381
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.034494   .0781428   -13.24   0.000    -1.187654   -.88
> 13348
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4127518   .5894409     0.70   0.484    -.7425498    1.5
> 68053
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.446831   1.008387    -2.43   0.015    -4.423266   -.47
> 03962
                   |
             _cons |   34.72107   .0116395  2983.03   0.000     34.69825    34.
> 74388
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74969       74969           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26018 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    202,042
Absorbing 1 HDFE group                            F(   5,  74968) =   51393.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9144
                                                  Adj R-squared   =     0.8639
                                                  Within R-sq.    =     0.7270
Number of clusters (mesa_code_elecspecific) =     74,969Root MSE  =     6.5039

                  (Std. err. adjusted for 74,969 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.37022   .0739571  -275.43   0.000    -20.51517   -20.
> 22526
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1949667   .0753557     2.59   0.010     .0472699    .34
> 26636
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7945871   .5892422     1.35   0.178     -.360325    1.9
> 49499
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.676292   1.008182    -3.65   0.000    -5.652325   -1.7
> 00259
                   |
            period |
                2  |  -14.11985   .0368294  -383.39   0.000    -14.19203   -14.
> 04766
                3  |          0  (omitted)
                   |
             _cons |   41.38088    .023858  1734.46   0.000     41.33412    41.
> 42764
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     74969       74969           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30602 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    113,424
Absorbing 1 HDFE group                            F(   4,  56711) =   10161.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9355
                                                  Adj R-squared   =     0.8709
                                                  Within R-sq.    =     0.4056
Number of clusters (mesa_code_elecspecific) =     56,712Root MSE  =     5.2593

                  (Std. err. adjusted for 56,712 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.026247   .0636721   -94.64   0.000    -6.151045    -5.
> 90145
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.1706738   .0726033    -2.35   0.019    -.3129767   -.02
> 83709
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.072334   .6934331     1.55   0.122    -.2867989    2.4
> 31467
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.934827   1.122026    -2.62   0.009    -5.134004   -.73
> 56496
                   |
             _cons |   28.13311   .0156161  1801.54   0.000      28.1025    28.
> 16372
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     56712       56712           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24973 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,065
Absorbing 1 HDFE group                            F(   4,  72784) =   44943.52
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8118
                                                  Adj R-squared   =     0.7007
                                                  Within R-sq.    =     0.4268
Number of clusters (mesa_code_elecspecific) =     72,785Root MSE  =     9.5544

                  (Std. err. adjusted for 72,785 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -13.02892   .0702415  -185.49   0.000    -13.16659   -12.
> 89124
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.276628   .0796859   -16.02   0.000    -1.432812   -1.1
> 20444
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .5132099   .5896232     0.87   0.384    -.6424496    1.6
> 68869
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.204697   1.008509    -2.19   0.029    -4.181371   -.22
> 80238
                   |
             _cons |   35.53552   .0117745  3018.01   0.000     35.51244     35
> .5586
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72785       72785           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24973 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    196,065
Absorbing 1 HDFE group                            F(   5,  72784) =   53603.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9139
                                                  Adj R-squared   =     0.8631
                                                  Within R-sq.    =     0.7378
Number of clusters (mesa_code_elecspecific) =     72,785Root MSE  =     6.4624

                  (Std. err. adjusted for 72,785 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.63403   .0754374  -273.53   0.000    -20.78188   -20.
> 48617
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.0134015   .0766841    -0.17   0.861    -.1637021    .13
> 68991
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .8960195   .5893967     1.52   0.128    -.2591961    2.0
> 51235
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.467924   1.008283    -3.44   0.001    -5.444155   -1.4
> 91692
                   |
            period |
                2  |   -14.4446   .0371787  -388.52   0.000    -14.51747   -14.
> 37173
                3  |          0  (omitted)
                   |
             _cons |   42.33781    .023918  1770.12   0.000     42.29093    42.
> 38469
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     72785       72785           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30993 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    115,078
Absorbing 1 HDFE group                            F(   4,  57538) =   10212.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9379
                                                  Adj R-squared   =     0.8757
                                                  Within R-sq.    =     0.4034
Number of clusters (mesa_code_elecspecific) =     57,539Root MSE  =     5.2104

                  (Std. err. adjusted for 57,539 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.076334   .0635543   -95.61   0.000      -6.2009   -5.9
> 51767
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0256317   .0721021     0.36   0.722    -.1156888    .16
> 69522
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |    1.12242    .693422     1.62   0.106    -.2366906    2.4
> 81531
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.131132   1.121993    -2.79   0.005    -5.330244   -.93
> 20199
                   |
             _cons |   27.14779   .0153593  1767.51   0.000     27.11768    27.
> 17789
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     57539       57539           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25149 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    199,267
Absorbing 1 HDFE group                            F(   4,  73916) =   43896.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8233
                                                  Adj R-squared   =     0.7190
                                                  Within R-sq.    =     0.4252
Number of clusters (mesa_code_elecspecific) =     73,917Root MSE  =     9.2945

                  (Std. err. adjusted for 73,917 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.70234   .0687575  -184.74   0.000     -12.8371   -12.
> 56757
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.137694    .078037   -14.58   0.000    -1.290646   -.98
> 47415
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .1866318   .5894481     0.32   0.752    -.9686842    1.3
> 41948
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.343632   1.008379    -2.32   0.020    -4.320051    -.3
> 67212
                   |
             _cons |   34.21967    .011526  2968.92   0.000     34.19708    34.
> 24227
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     73917       73917           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 25149 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    199,267
Absorbing 1 HDFE group                            F(   5,  73916) =   50640.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9155
                                                  Adj R-squared   =     0.8657
                                                  Within R-sq.    =     0.7253
Number of clusters (mesa_code_elecspecific) =     73,917Root MSE  =     6.4249

                  (Std. err. adjusted for 73,917 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -19.97037   .0737581  -270.75   0.000    -20.11494   -19.
> 82581
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1061209   .0753219     1.41   0.159    -.0415098    .25
> 37515
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .5622108   .5892475     0.95   0.340    -.5927121    1.7
> 17134
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.587446    1.00818    -3.56   0.000    -5.563475   -1.6
> 11417
                   |
            period |
                2  |  -13.78491   .0365998  -376.64   0.000    -13.85664   -13.
> 71317
                3  |          0  (omitted)
                   |
             _cons |   40.69394   .0235444  1728.39   0.000     40.64779    40.
> 74009
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     73917       73917           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 31922 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    117,434
Absorbing 1 HDFE group                            F(   4,  58716) =   10452.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9375
                                                  Adj R-squared   =     0.8750
                                                  Within R-sq.    =     0.4035
Number of clusters (mesa_code_elecspecific) =     58,717Root MSE  =     5.2107

                  (Std. err. adjusted for 58,717 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.047516   .0627116   -96.43   0.000    -6.170431   -5.9
> 24601
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.0191103   .0712011    -0.27   0.788    -.1586648    .12
> 04441
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.093603   .6933449     1.58   0.115    -.2653565    2.4
> 52562
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -3.08639   1.121935    -2.75   0.006    -5.285387   -.88
> 73928
                   |
             _cons |   27.32338   .0152054  1796.96   0.000     27.29357    27.
> 35318
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     58717       58717           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26048 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    203,242
Absorbing 1 HDFE group                            F(   4,  75511) =   44574.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8196
                                                  Adj R-squared   =     0.7130
                                                  Within R-sq.    =     0.4224
Number of clusters (mesa_code_elecspecific) =     75,512Root MSE  =     9.4385

                  (Std. err. adjusted for 75,512 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.87115   .0687543  -187.21   0.000    -13.00591   -12.
> 73639
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.087427   .0780724   -13.93   0.000    -1.240448    -.9
> 34405
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .3554448   .5894475     0.60   0.547    -.7998696    1.5
> 10759
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.393899   1.008382    -2.37   0.018    -4.370323   -.41
> 74751
                   |
             _cons |   34.52495   .0115563  2987.55   0.000      34.5023     34
> .5476
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75512       75512           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26048 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    203,242
Absorbing 1 HDFE group                            F(   5,  75511) =   51731.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9147
                                                  Adj R-squared   =     0.8643
                                                  Within R-sq.    =     0.7270
Number of clusters (mesa_code_elecspecific) =     75,512Root MSE  =     6.4890

                  (Std. err. adjusted for 75,512 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.28063   .0739548  -274.23   0.000    -20.42558   -20.
> 13567
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .1465083   .0752743     1.95   0.052     -.001029    .29
> 40455
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7301573   .5892429     1.24   0.215    -.4247562    1.8
> 85071
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.627834   1.008176    -3.60   0.000    -5.603854   -1.6
> 51813
                   |
            period |
                2  |  -14.06952   .0366718  -383.66   0.000     -14.1414   -13.
> 99765
                3  |          0  (omitted)
                   |
             _cons |   41.14889   .0237017  1736.11   0.000     41.10244    41.
> 19535
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75512       75512           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 30604 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    104,826
Absorbing 1 HDFE group                            F(   4,  52412) =    8993.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9388
                                                  Adj R-squared   =     0.8776
                                                  Within R-sq.    =     0.3982
Number of clusters (mesa_code_elecspecific) =     52,413Root MSE  =     5.3467

                  (Std. err. adjusted for 52,413 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.450834   .0668026   -96.57   0.000    -6.581768     -6
> .3199
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .4523373   .0762863     5.93   0.000     .3028154    .60
> 18592
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.496921    .693729     2.16   0.031     .1372054    2.8
> 56636
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.557838   1.122272    -3.17   0.002    -5.757502   -1.3
> 58173
                   |
             _cons |   27.29014   .0165138  1652.56   0.000     27.25777    27.
> 32251
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     52413       52413           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24022 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    183,670
Absorbing 1 HDFE group                            F(   4,  68530) =   37492.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8392
                                                  Adj R-squared   =     0.7435
                                                  Within R-sq.    =     0.4316
Number of clusters (mesa_code_elecspecific) =     68,531Root MSE  =     9.0088

                  (Std. err. adjusted for 68,531 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |    -12.796   .0732466  -174.70   0.000    -12.93956   -12.
> 65243
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -.6713108   .0830313    -8.09   0.000     -.834052   -.50
> 85697
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .2802908   .5899894     0.48   0.635    -.8760876    1.4
> 36669
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.810015    1.00878    -2.79   0.005    -4.787221    -.8
> 32808
                   |
             _cons |    34.0057   .0122816  2768.84   0.000     33.98163    34.
> 02977
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     68531       68531           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 24022 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    183,670
Absorbing 1 HDFE group                            F(   5,  68530) =   44470.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9185
                                                  Adj R-squared   =     0.8700
                                                  Within R-sq.    =     0.7121
Number of clusters (mesa_code_elecspecific) =     68,531Root MSE  =     6.4122

                  (Std. err. adjusted for 68,531 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -19.66007   .0789605  -248.99   0.000    -19.81484   -19.
> 50531
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .5912568    .080532     7.34   0.000     .4334141    .74
> 90995
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .6406406   .5898113     1.09   0.277    -.5153887     1.
> 79667
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -4.072582   1.008585    -4.04   0.000    -6.049408   -2.0
> 95757
                   |
            period |
                2  |  -13.00745   .0373018  -348.71   0.000    -13.08057   -12.
> 93434
                3  |          0  (omitted)
                   |
             _cons |   40.07552   .0241001  1662.88   0.000     40.02829    40.
> 12276
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     68531       68531           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 32067 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,204
Absorbing 1 HDFE group                            F(   4,  59101) =   10537.23
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4037
Number of clusters (mesa_code_elecspecific) =     59,102Root MSE  =     5.2221

                  (Std. err. adjusted for 59,102 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.080861   .0628739   -96.72   0.000    -6.204094   -5.9
> 57628
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0074079   .0712919     0.10   0.917    -.1323246    .14
> 71404
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.126948   .6933595     1.63   0.104    -.2320395    2.4
> 85936
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.112908    1.12194    -2.77   0.006    -5.311916   -.91
> 39004
                   |
             _cons |   27.39883   .0151889  1803.87   0.000     27.36906     27
> .4286
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59102       59102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26236 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,501
Absorbing 1 HDFE group                            F(   4,  75972) =   44921.53
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8199
                                                  Adj R-squared   =     0.7134
                                                  Within R-sq.    =     0.4229
Number of clusters (mesa_code_elecspecific) =     75,973Root MSE  =     9.4218

                  (Std. err. adjusted for 75,973 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.88045    .068714  -187.45   0.000    -13.01512   -12.
> 74577
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.059695   .0779349   -13.60   0.000    -1.212447   -.90
> 69429
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .3647388   .5894428     0.62   0.536    -.7905662    1.5
> 20044
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -2.42163   1.008371    -2.40   0.016    -4.398033    -.4
> 45228
                   |
             _cons |   34.57786   .0115098  3004.21   0.000      34.5553    34.
> 60042
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75973       75973           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26236 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,501
Absorbing 1 HDFE group                            F(   5,  75972) =   52059.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9146
                                                  Adj R-squared   =     0.8642
                                                  Within R-sq.    =     0.7265
Number of clusters (mesa_code_elecspecific) =     75,973Root MSE  =     6.4864

                  (Std. err. adjusted for 75,973 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.27311   .0738658  -274.46   0.000    -20.41789   -20.
> 12833
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |    .174534   .0751803     2.32   0.020     .0271809     .3
> 21887
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .7427249   .5892426     1.26   0.208    -.4121877    1.8
> 97638
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.655859   1.008169    -3.63   0.000    -5.631865   -1.6
> 79853
                   |
            period |
                2  |  -14.02936   .0365578  -383.76   0.000    -14.10101    -13
> .9577
                3  |          0  (omitted)
                   |
             _cons |   41.18341   .0236031  1744.83   0.000     41.13715    41.
> 22967
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     75973       75973           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 32106 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    118,204
Absorbing 1 HDFE group                            F(   4,  59101) =   10580.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9374
                                                  Adj R-squared   =     0.8747
                                                  Within R-sq.    =     0.4045
Number of clusters (mesa_code_elecspecific) =     59,102Root MSE  =     5.2239

                  (Std. err. adjusted for 59,102 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -6.125122   .0630641   -97.13   0.000    -6.248728   -6.0
> 01516
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .0539401    .071431     0.76   0.450    -.0860649    .19
> 39451
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   1.171208   .6933768     1.69   0.091    -.1878129     2.
> 53023
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |   -3.15944   1.121949    -2.82   0.005    -5.358466   -.96
> 04152
                   |
             _cons |   27.40359   .0151942  1803.56   0.000     27.37381    27.
> 43337
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     59102       59102           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26256 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,554
Absorbing 1 HDFE group                            F(   4,  75999) =   44959.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.8198
                                                  Adj R-squared   =     0.7133
                                                  Within R-sq.    =     0.4232
Number of clusters (mesa_code_elecspecific) =     76,000Root MSE  =     9.4321

                  (Std. err. adjusted for 76,000 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -12.93867   .0689393  -187.68   0.000    -13.07379   -12.
> 80355
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |  -1.010154   .0781405   -12.93   0.000    -1.163308   -.85
> 69986
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .4229602   .5894691     0.72   0.473    -.7323963    1.5
> 78317
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -2.471172   1.008387    -2.45   0.014    -4.447605   -.49
> 47382
                   |
             _cons |   34.59153    .011524  3001.69   0.000     34.56894    34.
> 61411
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76000       76000           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved
(dropped 26256 singleton observations)
note: 1bn.ep is probably collinear with the fixed effects (all partialled-out v
> alues are close to zero; tol = 1.0e-09)
note: 1bn.ciutadella is probably collinear with the fixed effects (all partiall
> ed-out values are close to zero; tol = 1.0e-09)
note: 1bn.ep#1bn.ciutadella is probably collinear with the fixed effects (all p
> artialled-out values are close to zero; tol = 1.0e-09)
(MWFE estimator converged in 1 iterations)
note: 1.ep omitted because of collinearity
note: 1.ciutadella omitted because of collinearity
note: 1.ep#1.ciutadella omitted because of collinearity
note: 3.period omitted because of collinearity

HDFE Linear regression                            Number of obs   =    204,554
Absorbing 1 HDFE group                            F(   5,  75999) =   52101.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9146
                                                  Adj R-squared   =     0.8642
                                                  Within R-sq.    =     0.7267
Number of clusters (mesa_code_elecspecific) =     76,000Root MSE  =     6.4921

                  (Std. err. adjusted for 76,000 clusters in mesa_code_elecspec
> ific)
-------------------------------------------------------------------------------
-----
                   |               Robust
      pp_voteshare | Coefficient  std. err.      t    P>|t|     [95% conf. inte
> rval]
-------------------+-----------------------------------------------------------
-----
            1.post |  -20.34266    .074094  -274.55   0.000    -20.48789   -20.
> 19744
              1.ep |          0  (omitted)
                   |
           post#ep |
              1 1  |   .2296582   .0753856     3.05   0.002     .0819029    .37
> 74136
                   |
      1.ciutadella |          0  (omitted)
                   |
   post#ciutadella |
              1 1  |   .8035429    .589269     1.36   0.173    -.3514214    1.9
> 58507
                   |
     ep#ciutadella |
              1 1  |          0  (omitted)
                   |
post#ep#ciutadella |
            1 1 1  |  -3.710984   1.008184    -3.68   0.000     -5.68702   -1.7
> 34947
                   |
            period |
                2  |  -14.04682   .0365658  -384.15   0.000    -14.11849   -13.
> 97516
                3  |          0  (omitted)
                   |
             _cons |   41.20477    .023623  1744.27   0.000     41.15847    41.
> 25107
-------------------------------------------------------------------------------
-----

Absorbed degrees of freedom:
----------------------------------------------------------------+
            Absorbed FE | Categories  - Redundant  = Num. Coefs |
------------------------+---------------------------------------|
 mesa_code_elecspecific |     76000       76000           0    *|
----------------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
file 01_data/jackknives_ddd.dta saved

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured6.do"

. ** NOTE: THIS DO-FILE IS PRESENTED WITH THE AIM OF BACKING THE CLAIM THAT THE
>  INTERACTION BETWEEN VOTING BOOTH USE AND MUNICIPALITY SIZE IS STATISTICALLY 
> SIGNIFICANT, AS REPORTED IN THE APPENDIX TEXT DISCUSSING FIGURE D.6
. 
. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. ** HTE based on municipality size
. regr cabine_use pp_dummy##c.TAMUNI, r

Linear regression                               Number of obs     =      1,847
                                                F(3, 1843)        =      76.07
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0865
                                                Root MSE          =     .47526

-------------------------------------------------------------------------------
----
                  |               Robust
       cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. inter
> val]
------------------+------------------------------------------------------------
----
       1.pp_dummy |   .2789992    .069667     4.00   0.000     .1423647    .415
> 6337
           TAMUNI |  -.0775385   .0065797   -11.78   0.000    -.0904428   -.064
> 6341
                  |
pp_dummy#c.TAMUNI |
               1  |  -.0412749   .0153465    -2.69   0.007    -.0713732   -.011
> 1765
                  |
            _cons |   .7301755   .0299819    24.35   0.000     .6713734    .788
> 9775
-------------------------------------------------------------------------------
----

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured7_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Fake model to start the data
. regr pp_dummy CCAA

      Source |       SS           df       MS      Number of obs   =     3,376
-------------+----------------------------------   F(1, 3374)      =      0.01
       Model |  .001511648         1  .001511648   Prob > F        =    0.9221
    Residual |  533.401332     3,374  .158091681   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0003
       Total |  533.402844     3,375  .158045287   Root MSE        =    .39761

------------------------------------------------------------------------------
    pp_dummy | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        CCAA |   .0001329   .0013588     0.10   0.922    -.0025313    .0027971
       _cons |   .1955201   .0137159    14.26   0.000     .1686279    .2224123
------------------------------------------------------------------------------

. regsave CCAA using 01_data/survey_data.dta, ci level(95) replace addlabel ///
> (Removed, fake, Model, fake,  FE, fake)
file 01_data/survey_data.dta saved

. 
. * Actual analyses
. regr cabine_use pp_dummy i.income age age_sq i.education i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(42, 1313)       =      20.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2486
                                                Root MSE          =     .43998

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0957879   .0348476     2.75   0.006     .0
> 274248                                                                       
>           .1641509
                                |
                         income |
         Menos o igual a 300 €  |   -.001077   .0901508    -0.01   0.990    -.1
> 779323                                                                       
>           .1757782
                De 301 a 600 €  |   .0023462   .0561697     0.04   0.967    -.1
> 078461                                                                       
>           .1125384
                De 601 a 900 €  |  -.0300031   .0442628    -0.68   0.498    -.1
> 168367                                                                       
>           .0568304
              De 901 a 1.200 €  |  -.0399661   .0416178    -0.96   0.337    -.1
> 216108                                                                       
>           .0416785
            De 1.201 a 1.800 €  |  -.0142827   .0429925    -0.33   0.740    -.0
> 986242                                                                       
>           .0700587
            De 1.801 a 2.400 €  |   .0151249    .050847     0.30   0.766    -.0
> 846254                                                                       
>           .1148752
            De 2.401 a 3.000 €  |  -.0189724   .0701883    -0.27   0.787    -.1
> 566659                                                                       
>            .118721
            De 3.001 a 4.500 €  |   .1608525   .1087852     1.48   0.139    -.0
> 525594                                                                       
>           .3742643
            De 4.501 a 6.000 €  |  -.4173938   .1726096    -2.42   0.016    -.7
> 560146                                                                       
>           -.078773
                Más de 6.000 €  |   .0347416   .2096841     0.17   0.868    -.3
> 766109                                                                       
>           .4460941
                                |
                            age |  -.0009516    .004497    -0.21   0.832    -.0
> 097737                                                                       
>           .0078705
                         age_sq |  -.0000138   .0000469    -0.29   0.769    -.0
> 001058                                                                       
>           .0000782
                                |
                      education |
                      Primaria  |   -.056612   .1050251    -0.54   0.590    -.2
> 626473                                                                       
>           .1494234
           Secundaria 1ª etapa  |  -.1352267    .105961    -1.28   0.202     -.
> 343098                                                                       
>           .0726446
           Secundaria 2ª etapa  |   -.164935   .1076425    -1.53   0.126    -.3
> 761051                                                                       
>            .046235
                          F.P.  |  -.0864042   .1068618    -0.81   0.419    -.2
> 960427                                                                       
>           .1232342
                    Superiores  |  -.1048523   .1082154    -0.97   0.333    -.3
> 171462                                                                       
>           .1074417
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0017008    .059567     0.03   0.977    -.1
> 151561                                                                       
>           .1185576
    10.001 a 50.000 habitantes  |  -.1301541   .0579844    -2.24   0.025    -.2
> 439062                                                                       
>          -.0164019
   50.001 a 100.000 habitantes  |  -.1793708   .0643594    -2.79   0.005    -.3
> 056294                                                                       
>          -.0531123
  100.001 a 400.000 habitantes  |  -.2218752   .0597661    -3.71   0.000    -.3
> 391226                                                                       
>          -.1046278
400.001 a 1.000.000 habitantes  |   -.385478   .0678563    -5.68   0.000    -.5
> 185966                                                                       
>          -.2523593
   Más de 1.000.000 habitantes  |  -.2440431   .0635046    -3.84   0.000    -.3
> 686246                                                                       
>          -.1194615
                                |
                           CCAA |
                        Aragón  |  -.0247428   .0687962    -0.36   0.719    -.1
> 597053                                                                       
>           .1102198
      Asturias (Principado de)  |  -.2284282   .0726127    -3.15   0.002    -.3
> 708778                                                                       
>          -.0859785
               Balears (Illes)  |  -.1880572   .0775644    -2.42   0.015    -.3
> 402208                                                                       
>          -.0358935
                      Canarias  |   .3629672   .0536087     6.77   0.000     .2
> 577992                                                                       
>           .4681353
                     Cantabria  |  -.0630006   .0685758    -0.92   0.358    -.1
> 975306                                                                       
>           .0715294
            Castilla-La Mancha  |   .0018541   .0711443     0.03   0.979    -.1
> 377148                                                                       
>            .141423
               Castilla y León  |   .0425821   .0711596     0.60   0.550     -.
> 097017                                                                       
>           .1821811
                      Cataluña  |   -.444581   .0481774    -9.23   0.000    -.5
> 390941                                                                       
>          -.3500679
          Comunitat Valenciana  |  -.0828788   .0544282    -1.52   0.128    -.1
> 896546                                                                       
>            .023897
                   Extremadura  |   .1510554     .06112     2.47   0.014     .0
> 311519                                                                       
>           .2709589
                       Galicia  |   -.032895    .072211    -0.46   0.649    -.1
> 745565                                                                       
>           .1087666
         Madrid (Comunidad de)  |  -.3992186   .0472524    -8.45   0.000    -.4
> 919171                                                                       
>          -.3065202
            Murcia (Región de)  |   .1317411   .0662411     1.99   0.047     .0
> 017911                                                                       
>            .261691
  Navarra (Comunidad Foral de)  |  -.2051692   .0911423    -2.25   0.025    -.3
> 839696                                                                       
>          -.0263689
                    País Vasco  |   -.121255   .0885573    -1.37   0.171    -.2
> 949842                                                                       
>           .0524743
                    Rioja (La)  |  -.0740735   .1061093    -0.70   0.485    -.2
> 822357                                                                       
>           .1340887
    Ceuta (Ciudad Autónoma de)  |   .2552348   .0872976     2.92   0.004     .0
> 839769                                                                       
>           .4264928
  Melilla (Ciudad Autónoma de)  |   .1304824   .1161583     1.12   0.262    -.0
> 973938                                                                       
>           .3583585
                                |
                          _cons |   .9206396   .1454832     6.33   0.000     .6
> 352345                                                                       
>           1.206045
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Female, Model, cabine_use, FE, With region fixed effects)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female age age_sq i.education i.TAMUNI  i.CCAA, r

Linear regression                               Number of obs     =      1,845
                                                F(33, 1810)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2598
                                                Root MSE          =     .43151

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0674998   .0291517     2.32   0.021     .0
> 103253                                                                       
>           .1246744
                         female |  -.0145121     .02034    -0.71   0.476    -.0
> 544044                                                                       
>           .0253803
                            age |  -.0021856   .0034763    -0.63   0.530    -.0
> 090034                                                                       
>           .0046323
                         age_sq |   9.29e-06   .0000361     0.26   0.797    -.0
> 000615                                                                       
>           .0000801
                                |
                      education |
                      Primaria  |  -.0019428   .0745737    -0.03   0.979    -.1
> 482024                                                                       
>           .1443168
           Secundaria 1ª etapa  |  -.0400532   .0745697    -0.54   0.591    -.1
> 863049                                                                       
>           .1061984
           Secundaria 2ª etapa  |  -.0787268   .0753213    -1.05   0.296    -.2
> 264527                                                                       
>            .068999
                          F.P.  |   -.023343    .074792    -0.31   0.755    -.1
> 700308                                                                       
>           .1233448
                    Superiores  |  -.0208023   .0738584    -0.28   0.778    -.1
> 656589                                                                       
>           .1240543
                         Otros  |   .0288464   .0832493     0.35   0.729    -.1
> 344285                                                                       
>           .1921212
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0291341   .0506066    -0.58   0.565    -.1
> 283876                                                                       
>           .0701194
    10.001 a 50.000 habitantes  |  -.1829577   .0480701    -3.81   0.000    -.2
> 772363                                                                       
>           -.088679
   50.001 a 100.000 habitantes  |  -.1905932   .0539498    -3.53   0.000    -.2
> 964036                                                                       
>          -.0847829
  100.001 a 400.000 habitantes  |  -.2439667   .0492202    -4.96   0.000     -.
> 340501                                                                       
>          -.1474324
400.001 a 1.000.000 habitantes  |  -.4011388   .0586422    -6.84   0.000    -.5
> 161523                                                                       
>          -.2861252
   Más de 1.000.000 habitantes  |    -.28522   .0505732    -5.64   0.000    -.3
> 844079                                                                       
>           -.186032
                                |
                           CCAA |
                        Aragón  |  -.0551116   .0616078    -0.89   0.371    -.1
> 759416                                                                       
>           .0657183
      Asturias (Principado de)  |  -.2207104   .0654879    -3.37   0.001    -.3
> 491502                                                                       
>          -.0922706
               Balears (Illes)  |  -.0924657   .0626674    -1.48   0.140    -.2
> 153738                                                                       
>           .0304424
                      Canarias  |   .3773672   .0488085     7.73   0.000     .2
> 816404                                                                       
>           .4730941
                     Cantabria  |  -.0575658   .0619314    -0.93   0.353    -.1
> 790304                                                                       
>           .0638989
            Castilla-La Mancha  |   .0361605   .0648208     0.56   0.577     -.
> 090971                                                                       
>           .1632921
               Castilla y León  |  -.0263129   .0638826    -0.41   0.680    -.1
> 516043                                                                       
>           .0989785
                      Cataluña  |  -.4658812   .0367563   -12.67   0.000    -.5
> 379705                                                                       
>           -.393792
          Comunitat Valenciana  |  -.0647434   .0504271    -1.28   0.199    -.1
> 636449                                                                       
>           .0341581
                   Extremadura  |   .1306415   .0585139     2.23   0.026     .0
> 158796                                                                       
>           .2454033
                       Galicia  |  -.0714428   .0623494    -1.15   0.252    -.1
> 937271                                                                       
>           .0508415
         Madrid (Comunidad de)  |  -.3907392   .0411273    -9.50   0.000    -.4
> 714011                                                                       
>          -.3100772
            Murcia (Región de)  |   .1709927   .0612192     2.79   0.005     .0
> 509249                                                                       
>           .2910604
  Navarra (Comunidad Foral de)  |  -.1780008   .0840119    -2.12   0.034    -.3
> 427713                                                                       
>          -.0132303
                    País Vasco  |  -.1221997   .0757116    -1.61   0.107     -.
> 270691                                                                       
>           .0262916
                    Rioja (La)  |   .0226474    .070068     0.32   0.747    -.1
> 147752                                                                       
>             .16007
    Ceuta (Ciudad Autónoma de)  |   .2973934   .0711654     4.18   0.000     .1
> 578184                                                                       
>           .4369683
  Melilla (Ciudad Autónoma de)  |   .1273588   .1165308     1.09   0.275    -.1
> 011903                                                                       
>           .3559079
                                |
                          _cons |   .8608997   .1122623     7.67   0.000     .6
> 407224                                                                       
>           1.081077
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Income, Model, cabine_use, FE, With region fixed effects)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income i.education i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(41, 1314)       =      20.11
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2456
                                                Root MSE          =     .44072

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0864787   .0343256     2.52   0.012     .0
> 191399                                                                       
>           .1538176
                         female |  -.0226514   .0258262    -0.88   0.381    -.0
> 733164                                                                       
>           .0280136
                                |
                         income |
         Menos o igual a 300 €  |  -.0086103    .089364    -0.10   0.923     -.
> 183922                                                                       
>           .1667015
                De 301 a 600 €  |  -.0149642   .0556575    -0.27   0.788    -.1
> 241515                                                                       
>            .094223
                De 601 a 900 €  |   -.052723   .0433626    -1.22   0.224    -.1
> 377904                                                                       
>           .0323444
              De 901 a 1.200 €  |  -.0636647   .0405498    -1.57   0.117    -.1
> 432141                                                                       
>           .0158847
            De 1.201 a 1.800 €  |  -.0478666    .041196    -1.16   0.245    -.1
> 286838                                                                       
>           .0329505
            De 1.801 a 2.400 €  |  -.0314156   .0496384    -0.63   0.527    -.1
> 287947                                                                       
>           .0659635
            De 2.401 a 3.000 €  |  -.0719645   .0696943    -1.03   0.302    -.2
> 086888                                                                       
>           .0647598
            De 3.001 a 4.500 €  |   .1204304   .1077805     1.12   0.264    -.0
> 910103                                                                       
>           .3318711
            De 4.501 a 6.000 €  |  -.4588351   .1931996    -2.37   0.018    -.8
> 378484                                                                       
>          -.0798218
                Más de 6.000 €  |  -.0296177   .2056712    -0.14   0.886    -.4
> 330974                                                                       
>           .3738621
                                |
                      education |
                      Primaria  |  -.0361325   .1039995    -0.35   0.728    -.2
> 401556                                                                       
>           .1678906
           Secundaria 1ª etapa  |  -.0755646   .1009385    -0.75   0.454    -.2
> 735828                                                                       
>           .1224536
           Secundaria 2ª etapa  |  -.0940878   .1019135    -0.92   0.356    -.2
> 940187                                                                       
>           .1058431
                          F.P.  |  -.0132511   .1004976    -0.13   0.895    -.2
> 104044                                                                       
>           .1839023
                    Superiores  |  -.0259673   .1019739    -0.25   0.799    -.2
> 260168                                                                       
>           .1740821
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0145147   .0588443     0.25   0.805    -.1
> 009244                                                                       
>           .1299537
    10.001 a 50.000 habitantes  |  -.1211587   .0573144    -2.11   0.035    -.2
> 335964                                                                       
>          -.0087209
   50.001 a 100.000 habitantes  |  -.1724744   .0641104    -2.69   0.007    -.2
> 982443                                                                       
>          -.0467045
  100.001 a 400.000 habitantes  |  -.2197435   .0595873    -3.69   0.000    -.3
> 366401                                                                       
>          -.1028468
400.001 a 1.000.000 habitantes  |  -.3863474   .0678011    -5.70   0.000    -.5
> 193576                                                                       
>          -.2533371
   Más de 1.000.000 habitantes  |  -.2403842   .0636219    -3.78   0.000    -.3
> 651957                                                                       
>          -.1155727
                                |
                           CCAA |
                        Aragón  |  -.0217196   .0689675    -0.31   0.753     -.
> 157018                                                                       
>           .1135787
      Asturias (Principado de)  |  -.2292904   .0738414    -3.11   0.002    -.3
> 741503                                                                       
>          -.0844306
               Balears (Illes)  |  -.1826146   .0781938    -2.34   0.020    -.3
> 360129                                                                       
>          -.0292163
                      Canarias  |   .3673781   .0544255     6.75   0.000     .2
> 606077                                                                       
>           .4741485
                     Cantabria  |  -.0703577   .0681678    -1.03   0.302    -.2
> 040874                                                                       
>           .0633719
            Castilla-La Mancha  |  -.0001302   .0706644    -0.00   0.999    -.1
> 387575                                                                       
>           .1384971
               Castilla y León  |   .0395916   .0703832     0.56   0.574    -.0
> 984841                                                                       
>           .1776674
                      Cataluña  |  -.4454561    .048154    -9.25   0.000    -.5
> 399233                                                                       
>          -.3509889
          Comunitat Valenciana  |  -.0866453    .054465    -1.59   0.112    -.1
> 934932                                                                       
>           .0202026
                   Extremadura  |   .1503952   .0611948     2.46   0.014      .
> 030345                                                                       
>           .2704454
                       Galicia  |  -.0455742   .0719359    -0.63   0.526     -.
> 186696                                                                       
>           .0955476
         Madrid (Comunidad de)  |  -.4029481   .0469567    -8.58   0.000    -.4
> 950664                                                                       
>          -.3108298
            Murcia (Región de)  |   .1334052   .0663566     2.01   0.045     .0
> 032288                                                                       
>           .2635816
  Navarra (Comunidad Foral de)  |  -.2178523   .0909574    -2.40   0.017    -.3
> 962899                                                                       
>          -.0394147
                    País Vasco  |  -.1294142   .0891005    -1.45   0.147     -.
> 304209                                                                       
>           .0453807
                    Rioja (La)  |  -.0750915   .1060319    -0.71   0.479    -.2
> 831017                                                                       
>           .1329188
    Ceuta (Ciudad Autónoma de)  |   .2452185   .0892339     2.75   0.006      .
> 070162                                                                       
>           .4202749
  Melilla (Ciudad Autónoma de)  |    .137509   .1153538     1.19   0.233    -.0
> 887888                                                                       
>           .3638068
                                |
                          _cons |   .8141097   .1153003     7.06   0.000     .5
> 879169                                                                       
>           1.040302
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Age and age squared, Model, cabine_use, FE, With region fixed effec
> ts)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income age age_sq i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,357
                                                F(38, 1318)       =      21.90
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2433
                                                Root MSE          =     .44085

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0953134   .0348335     2.74   0.006     .0
> 269783                                                                       
>           .1636485
                         female |  -.0118322   .0255946    -0.46   0.644    -.0
> 620428                                                                       
>           .0383783
                                |
                         income |
         Menos o igual a 300 €  |  -.0102937   .0895186    -0.11   0.908    -.1
> 859082                                                                       
>           .1653207
                De 301 a 600 €  |   .0009798   .0570797     0.02   0.986    -.1
> 109973                                                                       
>           .1129568
                De 601 a 900 €  |   -.022245   .0447644    -0.50   0.619    -.1
> 100623                                                                       
>           .0655722
              De 901 a 1.200 €  |  -.0379871   .0424676    -0.89   0.371    -.1
> 212987                                                                       
>           .0453244
            De 1.201 a 1.800 €  |  -.0166412    .043464    -0.38   0.702    -.1
> 019073                                                                       
>           .0686249
            De 1.801 a 2.400 €  |   .0083603   .0502282     0.17   0.868    -.0
> 901758                                                                       
>           .1068963
            De 2.401 a 3.000 €  |  -.0233192   .0709317    -0.33   0.742    -.1
> 624706                                                                       
>           .1158323
            De 3.001 a 4.500 €  |   .1629351   .1079003     1.51   0.131    -.0
> 487399                                                                       
>           .3746101
            De 4.501 a 6.000 €  |  -.4100054   .1794578    -2.28   0.022    -.7
> 620595                                                                       
>          -.0579514
                Más de 6.000 €  |   .0466677   .2101682     0.22   0.824     -.
> 365633                                                                       
>           .4589683
                                |
                            age |  -.0017396   .0044334    -0.39   0.695    -.0
> 104369                                                                       
>           .0069577
                         age_sq |  -7.26e-08   .0000453    -0.00   0.999    -.0
> 000889                                                                       
>           .0000888
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0091586   .0597221    -0.15   0.878    -.1
> 263194                                                                       
>           .1080022
    10.001 a 50.000 habitantes  |   -.138285   .0577692    -2.39   0.017    -.2
> 516146                                                                       
>          -.0249554
   50.001 a 100.000 habitantes  |  -.1878824   .0642296    -2.93   0.004    -.3
> 138857                                                                       
>          -.0618791
  100.001 a 400.000 habitantes  |  -.2286637   .0595941    -3.84   0.000    -.3
> 455732                                                                       
>          -.1117541
400.001 a 1.000.000 habitantes  |  -.4023018   .0673519    -5.97   0.000    -.5
> 344305                                                                       
>          -.2701732
   Más de 1.000.000 habitantes  |  -.2426352   .0634106    -3.83   0.000     -.
> 367032                                                                       
>          -.1182384
                                |
                           CCAA |
                        Aragón  |  -.0283901   .0687772    -0.41   0.680    -.1
> 633147                                                                       
>           .1065346
      Asturias (Principado de)  |  -.2312678   .0728832    -3.17   0.002    -.3
> 742475                                                                       
>          -.0882881
               Balears (Illes)  |  -.1874219   .0776015    -2.42   0.016    -.3
> 396578                                                                       
>          -.0351859
                      Canarias  |    .365054   .0538801     6.78   0.000     .2
> 593538                                                                       
>           .4707542
                     Cantabria  |  -.0687249   .0688453    -1.00   0.318    -.2
> 037833                                                                       
>           .0663334
            Castilla-La Mancha  |  -.0108389    .071637    -0.15   0.880     -.
> 151374                                                                       
>           .1296961
               Castilla y León  |   .0451764   .0714816     0.63   0.527    -.0
> 950538                                                                       
>           .1854065
                      Cataluña  |  -.4490346   .0481205    -9.33   0.000    -.5
> 434358                                                                       
>          -.3546335
          Comunitat Valenciana  |  -.0897935   .0540213    -1.66   0.097    -.1
> 957706                                                                       
>           .0161836
                   Extremadura  |   .1491417    .061114     2.44   0.015     .0
> 292504                                                                       
>           .2690329
                       Galicia  |   -.038424   .0723623    -0.53   0.596    -.1
> 803819                                                                       
>            .103534
         Madrid (Comunidad de)  |  -.4129516   .0468618    -8.81   0.000    -.5
> 048834                                                                       
>          -.3210199
            Murcia (Región de)  |   .1339735    .066263     2.02   0.043      .
> 003981                                                                       
>           .2639661
  Navarra (Comunidad Foral de)  |  -.2044968   .0914296    -2.24   0.025    -.3
> 838602                                                                       
>          -.0251335
                    País Vasco  |  -.1146469    .088759    -1.29   0.197    -.2
> 887712                                                                       
>           .0594774
                    Rioja (La)  |  -.0938742   .1044198    -0.90   0.369    -.2
> 987214                                                                       
>            .110973
    Ceuta (Ciudad Autónoma de)  |    .238153   .0872135     2.73   0.006     .0
> 670606                                                                       
>           .4092455
  Melilla (Ciudad Autónoma de)  |   .1249712   .1161897     1.08   0.282    -.1
> 029656                                                                       
>           .3529081
                                |
                          _cons |   .8303985   .1144081     7.26   0.000     .6
> 059566                                                                       
>            1.05484
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Education, Model, cabine_use, FE, With region fixed effects)
(variable Removed was str9, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income age age_sq i.education i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(37, 1318)       =      16.16
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2079
                                                Root MSE          =     .45088

-------------------------------------------------------------------------------
----------------
                              |               Robust
                   cabine_use | Coefficient  std. err.      t    P>|t|     [95%
>  con                                                                         
>     f. interval]
------------------------------+------------------------------------------------
----------------
                     pp_dummy |   .1028783   .0366391     2.81   0.005      .03
> 1001                                                                         
>         .1747556
                       female |  -.0160273   .0265946    -0.60   0.547    -.068
> 1997                                                                         
>          .036145
                              |
                       income |
       Menos o igual a 300 €  |  -.0192186   .0920506    -0.21   0.835    -.199
> 8004                                                                         
>         .1613632
              De 301 a 600 €  |   .0023233    .056357     0.04   0.967    -.108
> 2359                                                                         
>         .1128825
              De 601 a 900 €  |   -.040951   .0458988    -0.89   0.372    -.130
> 9937                                                                         
>         .0490917
            De 901 a 1.200 €  |  -.0465194   .0426387    -1.09   0.275    -.130
> 1665                                                                         
>         .0371277
          De 1.201 a 1.800 €  |  -.0286426   .0450929    -0.64   0.525    -.117
> 1044                                                                         
>         .0598191
          De 1.801 a 2.400 €  |   .0181631   .0542462     0.33   0.738    -.088
> 2552                                                                         
>         .1245813
          De 2.401 a 3.000 €  |  -.0601569   .0732573    -0.82   0.412    -.203
> 8706                                                                         
>         .0835567
          De 3.001 a 4.500 €  |   .1454376   .1169574     1.24   0.214    -.084
> 0053                                                                         
>         .3748805
          De 4.501 a 6.000 €  |  -.4516595    .220487    -2.05   0.041    -.884
> 2033                                                                         
>        -.0191158
              Más de 6.000 €  |   .0620391   .1814303     0.34   0.732    -.293
> 8845                                                                         
>         .4179628
                              |
                          age |  -.0006323   .0045696    -0.14   0.890    -.009
> 5968                                                                         
>         .0083321
                       age_sq |  -.0000249   .0000479    -0.52   0.603     -.00
> 0119                                                                         
>         .0000691
                              |
                    education |
                    Primaria  |   -.083871   .1111912    -0.75   0.451    -.302
> 0022                                                                         
>         .1342602
         Secundaria 1ª etapa  |  -.1902146   .1120268    -1.70   0.090    -.409
> 9849                                                                         
>         .0295556
         Secundaria 2ª etapa  |   -.239317   .1133744    -2.11   0.035     -.46
> 1731                                                                         
>        -.0169029
                        F.P.  |  -.1535364   .1128089    -1.36   0.174    -.374
> 8409                                                                         
>         .0677682
                  Superiores  |  -.1880361   .1139357    -1.65   0.099    -.411
> 5511                                                                         
>          .035479
                              |
                         CCAA |
                      Aragón  |  -.0444904   .0737706    -0.60   0.547     -.18
> 9211                                                                         
>         .1002303
    Asturias (Principado de)  |  -.2290086   .0724692    -3.16   0.002     -.37
> 1176                                                                         
>        -.0868411
             Balears (Illes)  |  -.2524172   .0749139    -3.37   0.001    -.399
> 3808                                                                         
>        -.1054537
                    Canarias  |   .3724001   .0540057     6.90   0.000     .266
> 4536                                                                         
>         .4783467
                   Cantabria  |   .0313388   .0697236     0.45   0.653    -.105
> 4425                                                                         
>         .1681201
          Castilla-La Mancha  |   .0561067   .0727523     0.77   0.441    -.086
> 6163                                                                         
>         .1988296
             Castilla y León  |   .1035009   .0727375     1.42   0.155     -.03
> 9193                                                                         
>         .2461947
                    Cataluña  |  -.4189863   .0448254    -9.35   0.000    -.506
> 9232                                                                         
>        -.3310494
        Comunitat Valenciana  |  -.0752346   .0555555    -1.35   0.176    -.184
> 2215                                                                         
>         .0337522
                 Extremadura  |   .2241791   .0602339     3.72   0.000     .106
> 0143                                                                         
>         .3423439
                     Galicia  |    .037059   .0728198     0.51   0.611    -.105
> 7963                                                                         
>         .1799144
       Madrid (Comunidad de)  |  -.4035885   .0442189    -9.13   0.000    -.490
> 3356                                                                         
>        -.3168414
          Murcia (Región de)  |    .088626   .0668626     1.33   0.185    -.042
> 5427                                                                         
>         .2197948
Navarra (Comunidad Foral de)  |  -.0926747   .0916679    -1.01   0.312    -.272
> 5057                                                                         
>         .0871563
                  País Vasco  |   -.085018   .0872441    -0.97   0.330    -.256
> 1704                                                                         
>         .0861344
                  Rioja (La)  |  -.0447326   .1081456    -0.41   0.679     -.25
> 6889                                                                         
>         .1674237
  Ceuta (Ciudad Autónoma de)  |   .2551961    .079848     3.20   0.001      .09
> 8553                                                                         
>         .4118392
Melilla (Ciudad Autónoma de)  |   .1203762   .1109581     1.08   0.278    -.097
> 2976                                                                         
>           .33805
                              |
                        _cons |   .8311999   .1369459     6.07   0.000     .562
> 5441                                                                         
>         1.099856
-------------------------------------------------------------------------------
----------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Mun Size, Model, cabine_use, FE, With region fixed effects)
(variable Removed was str8, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy i.income age age_sq  i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,356
                                                F(24, 1331)       =      16.85
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1165
                                                Root MSE          =     .47387

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1309627   .0373478     3.51   0.000     .0
> 576957                                                                       
>           .2042297
                                |
                         income |
         Menos o igual a 300 €  |   .0384867   .0914337     0.42   0.674    -.1
> 408832                                                                       
>           .2178567
                De 301 a 600 €  |   .0041144   .0585368     0.07   0.944      -
> .11072                                                                       
>           .1189488
                De 601 a 900 €  |  -.0227361   .0480716    -0.47   0.636    -.1
> 170405                                                                       
>           .0715684
              De 901 a 1.200 €  |  -.0526532   .0452521    -1.16   0.245    -.1
> 414263                                                                       
>           .0361199
            De 1.201 a 1.800 €  |   -.051159   .0461904    -1.11   0.268     -.
> 141773                                                                       
>           .0394549
            De 1.801 a 2.400 €  |   -.029117   .0559339    -0.52   0.603    -.1
> 388452                                                                       
>           .0806113
            De 2.401 a 3.000 €  |  -.1108693   .0771249    -1.44   0.151    -.2
> 621689                                                                       
>           .0404302
            De 3.001 a 4.500 €  |   .1019697   .1092574     0.93   0.351    -.1
> 123657                                                                       
>           .3163051
            De 4.501 a 6.000 €  |  -.4901884   .0770843    -6.36   0.000    -.6
> 414084                                                                       
>          -.3389684
                Más de 6.000 €  |   -.082291   .2505006    -0.33   0.743    -.5
> 737099                                                                       
>            .409128
                                |
                            age |   .0023355   .0047417     0.49   0.622    -.0
> 069665                                                                       
>           .0116376
                         age_sq |  -.0000509   .0000488    -1.04   0.298    -.0
> 001467                                                                       
>            .000045
                                |
                      education |
                      Primaria  |  -.0629371   .1145796    -0.55   0.583    -.2
> 877135                                                                       
>           .1618393
           Secundaria 1ª etapa  |  -.1594793    .114485    -1.39   0.164    -.3
> 840701                                                                       
>           .0651114
           Secundaria 2ª etapa  |  -.2281797   .1159436    -1.97   0.049    -.4
> 556318                                                                       
>          -.0007276
                          F.P.  |  -.1197025   .1152759    -1.04   0.299    -.3
> 458447                                                                       
>           .1064397
                    Superiores  |  -.1337901   .1167254    -1.15   0.252    -.3
> 627759                                                                       
>           .0951957
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0093359   .0625942     0.15   0.881    -.1
> 134581                                                                       
>             .13213
    10.001 a 50.000 habitantes  |  -.1271295   .0600733    -2.12   0.035    -.2
> 449782                                                                       
>          -.0092809
   50.001 a 100.000 habitantes  |  -.1215937   .0638493    -1.90   0.057    -.2
> 468498                                                                       
>           .0036625
  100.001 a 400.000 habitantes  |   -.241599   .0609706    -3.96   0.000     -.
> 361208                                                                       
>          -.1219901
400.001 a 1.000.000 habitantes  |  -.3247061   .0664179    -4.89   0.000    -.4
> 550012                                                                       
>           -.194411
   Más de 1.000.000 habitantes  |   -.564044    .060347    -9.35   0.000    -.6
> 824296                                                                       
>          -.4456583
                                |
                          _cons |   .8153522   .1541388     5.29   0.000     .5
> 129707                                                                       
>           1.117734
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Female, Model, cabine_use, FE, Without region fixed effects)
(variable Removed was str6, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female age age_sq  i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,845
                                                F(15, 1828)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1085
                                                Root MSE          =     .47124

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1255689   .0311194     4.04   0.000     .0
> 645356                                                                       
>           .1866023
                         female |  -.0098497   .0221311    -0.45   0.656    -.0
> 532545                                                                       
>           .0335551
                            age |  -.0017269   .0037415    -0.46   0.644    -.0
> 090649                                                                       
>           .0056111
                         age_sq |  -5.04e-06   .0000385    -0.13   0.896    -.0
> 000806                                                                       
>           .0000705
                                |
                      education |
                      Primaria  |  -.0011471   .0827992    -0.01   0.989    -.1
> 635381                                                                       
>            .161244
           Secundaria 1ª etapa  |  -.0559863    .080948    -0.69   0.489    -.2
> 147466                                                                       
>            .102774
           Secundaria 2ª etapa  |  -.1382301   .0817678    -1.69   0.091    -.2
> 985983                                                                       
>            .022138
                          F.P.  |  -.0651544   .0811524    -0.80   0.422    -.2
> 243155                                                                       
>           .0940066
                    Superiores  |  -.0619717   .0802831    -0.77   0.440    -.2
> 194279                                                                       
>           .0954846
                         Otros  |   .4701996   .0814924     5.77   0.000     .3
> 103716                                                                       
>           .6300276
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0386395   .0538224    -0.72   0.473    -.1
> 441994                                                                       
>           .0669205
    10.001 a 50.000 habitantes  |  -.1839573   .0503451    -3.65   0.000    -.2
> 826972                                                                       
>          -.0852174
   50.001 a 100.000 habitantes  |  -.1378566   .0544493    -2.53   0.011    -.2
> 446459                                                                       
>          -.0310672
  100.001 a 400.000 habitantes  |  -.2484199   .0510168    -4.87   0.000    -.3
> 484773                                                                       
>          -.1483625
400.001 a 1.000.000 habitantes  |  -.3106505   .0577796    -5.38   0.000    -.4
> 239716                                                                       
>          -.1973295
   Más de 1.000.000 habitantes  |  -.5995204   .0482926   -12.41   0.000    -.6
> 942349                                                                       
>          -.5048058
                                |
                          _cons |   .7965084   .1203129     6.62   0.000     .5
> 605433                                                                       
>           1.032474
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Income, Model, cabine_use, FE, Without region fixed effects)
(variable Removed was str6, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income  i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,356
                                                F(23, 1332)       =      20.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1121
                                                Root MSE          =     .47488

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1224569   .0368658     3.32   0.001     .0
> 501356                                                                       
>           .1947783
                         female |  -.0209528   .0275981    -0.76   0.448    -.0
> 750932                                                                       
>           .0331875
                                |
                         income |
         Menos o igual a 300 €  |   .0343946   .0911012     0.38   0.706    -.1
> 443229                                                                       
>           .2131121
                De 301 a 600 €  |  -.0082742   .0583012    -0.14   0.887    -.1
> 226464                                                                       
>            .106098
                De 601 a 900 €  |  -.0423855   .0474336    -0.89   0.372    -.1
> 354381                                                                       
>           .0506672
              De 901 a 1.200 €  |  -.0706219   .0442215    -1.60   0.111    -.1
> 573733                                                                       
>           .0161294
            De 1.201 a 1.800 €  |  -.0774796   .0446761    -1.73   0.083    -.1
> 651227                                                                       
>           .0101636
            De 1.801 a 2.400 €  |  -.0686095   .0546098    -1.26   0.209    -.1
> 757401                                                                       
>           .0385211
            De 2.401 a 3.000 €  |  -.1568221   .0756065    -2.07   0.038    -.3
> 051429                                                                       
>          -.0085013
            De 3.001 a 4.500 €  |   .0691292    .108312     0.64   0.523    -.1
> 433514                                                                       
>           .2816099
            De 4.501 a 6.000 €  |  -.5219331   .0587615    -8.88   0.000    -.6
> 372082                                                                       
>          -.4066581
                Más de 6.000 €  |  -.1434336   .2456946    -0.58   0.559    -.6
> 254241                                                                       
>            .338557
                                |
                      education |
                      Primaria  |  -.0320781   .1118255    -0.29   0.774    -.2
> 514513                                                                       
>           .1872951
           Secundaria 1ª etapa  |   -.077552   .1081084    -0.72   0.473    -.2
> 896332                                                                       
>           .1345292
           Secundaria 2ª etapa  |  -.1375996   .1091946    -1.26   0.208    -.3
> 518118                                                                       
>           .0766126
                          F.P.  |  -.0242251   .1078487    -0.22   0.822     -.
> 235797                                                                       
>           .1873468
                    Superiores  |   -.033265   .1091087    -0.30   0.761    -.2
> 473087                                                                       
>           .1807786
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0194469   .0621772     0.31   0.755     -.
> 102529                                                                       
>           .1414228
    10.001 a 50.000 habitantes  |  -.1194222   .0595675    -2.00   0.045    -.2
> 362786                                                                       
>          -.0025659
   50.001 a 100.000 habitantes  |   -.116029    .063584    -1.82   0.068    -.2
> 407647                                                                       
>           .0087067
  100.001 a 400.000 habitantes  |  -.2402308   .0608223    -3.95   0.000    -.3
> 595486                                                                       
>           -.120913
400.001 a 1.000.000 habitantes  |  -.3247101   .0665002    -4.88   0.000    -.4
> 551667                                                                       
>          -.1942534
   Más de 1.000.000 habitantes  |  -.5642708   .0602846    -9.36   0.000    -.6
> 825338                                                                       
>          -.4460078
                                |
                          _cons |   .7455011   .1197144     6.23   0.000     .5
> 106518                                                                       
>           .9803504
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Age and age squared, Model, cabine_use, FE, Without region fixed ef
> fects)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income age age_sq i.TAMUNI, r

Linear regression                               Number of obs     =      1,357
                                                F(20, 1336)       =      20.08
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1076
                                                Root MSE          =     .47552

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1281729   .0374295     3.42   0.001      .
> 054746                                                                       
>           .2015998
                         female |  -.0119173   .0273853    -0.44   0.664    -.0
> 656401                                                                       
>           .0418055
                                |
                         income |
         Menos o igual a 300 €  |   .0274461   .0914479     0.30   0.764     -.
> 151951                                                                       
>           .2068431
                De 301 a 600 €  |   .0043346   .0598821     0.07   0.942    -.1
> 131386                                                                       
>           .1218079
                De 601 a 900 €  |  -.0094285   .0486272    -0.19   0.846    -.1
> 048226                                                                       
>           .0859656
              De 901 a 1.200 €  |  -.0497551   .0459995    -1.08   0.280    -.1
> 399942                                                                       
>           .0404841
            De 1.201 a 1.800 €  |  -.0551222   .0467639    -1.18   0.239    -.1
> 468609                                                                       
>           .0366165
            De 1.801 a 2.400 €  |  -.0359879   .0547123    -0.66   0.511    -.1
> 433192                                                                       
>           .0713434
            De 2.401 a 3.000 €  |  -.1171892   .0775714    -1.51   0.131    -.2
> 693642                                                                       
>           .0349858
            De 3.001 a 4.500 €  |   .1040575   .1076192     0.97   0.334    -.1
> 070636                                                                       
>           .3151787
            De 4.501 a 6.000 €  |  -.4783845   .0635572    -7.53   0.000    -.6
> 030672                                                                       
>          -.3537018
                Más de 6.000 €  |  -.0710014   .2504963    -0.28   0.777    -.5
> 624103                                                                       
>           .4204074
                                |
                            age |   .0016945   .0047413     0.36   0.721    -.0
> 076067                                                                       
>           .0109957
                         age_sq |  -.0000355   .0000482    -0.74   0.461      -
> .00013                                                                       
>            .000059
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0051268   .0627265    -0.08   0.935    -.1
> 281801                                                                       
>           .1179264
    10.001 a 50.000 habitantes  |  -.1389096   .0597338    -2.33   0.020    -.2
> 560919                                                                       
>          -.0217273
   50.001 a 100.000 habitantes  |  -.1393537   .0636152    -2.19   0.029    -.2
> 641501                                                                       
>          -.0145572
  100.001 a 400.000 habitantes  |  -.2542914   .0605593    -4.20   0.000     -.
> 373093                                                                       
>          -.1354899
400.001 a 1.000.000 habitantes  |  -.3471865   .0657148    -5.28   0.000     -.
> 476102                                                                       
>           -.218271
   Más de 1.000.000 habitantes  |  -.5718232   .0601731    -9.50   0.000    -.6
> 898673                                                                       
>          -.4537792
                                |
                          _cons |   .6828453   .1169791     5.84   0.000     .4
> 533625                                                                       
>            .912328
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Education, Model, cabine_use, FE, Without region fixed effects)
(variable Removed was str9, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
. regr cabine_use pp_dummy female i.income age age_sq i.education, r

Linear regression                               Number of obs     =      1,356
                                                F(19, 1336)       =      38.00
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0371
                                                Root MSE          =     .49377

-------------------------------------------------------------------------------
---------
                       |               Robust
            cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. 
> interval]
-----------------------+-------------------------------------------------------
---------
              pp_dummy |   .1444323   .0399454     3.62   0.000     .0660698   
>  .2227947
                female |  -.0298681   .0288943    -1.03   0.301    -.0865512   
>   .026815
                       |
                income |
Menos o igual a 300 €  |   .0181334   .0936736     0.19   0.847      -.16563   
>  .2018968
       De 301 a 600 €  |    .000288    .059473     0.00   0.996    -.1163826   
>  .1169586
       De 601 a 900 €  |  -.0458199   .0499288    -0.92   0.359    -.1437672   
>  .0521275
     De 901 a 1.200 €  |   -.083785   .0470618    -1.78   0.075    -.1761082   
>  .0085381
   De 1.201 a 1.800 €  |  -.0991409    .049104    -2.02   0.044    -.1954702   
> -.0028116
   De 1.801 a 2.400 €  |  -.0589297   .0604075    -0.98   0.329    -.1774336   
>  .0595743
   De 2.401 a 3.000 €  |  -.2054812   .0823241    -2.50   0.013    -.3669797   
> -.0439827
   De 3.001 a 4.500 €  |   .0670382   .1111624     0.60   0.547    -.1510337   
>    .28511
   De 4.501 a 6.000 €  |  -.5142531   .0520049    -9.89   0.000    -.6162732   
>  -.412233
       Más de 6.000 €  |  -.0395171   .2324089    -0.17   0.865    -.4954431   
>   .416409
                       |
                   age |   .0040843   .0048537     0.84   0.400    -.0054375   
>   .013606
                age_sq |  -.0000774   .0000501    -1.54   0.123    -.0001757   
>   .000021
                       |
             education |
             Primaria  |  -.0848678   .1249759    -0.68   0.497    -.3300381   
>  .1603024
  Secundaria 1ª etapa  |  -.2150703   .1240375    -1.73   0.083    -.4583998   
>  .0282591
  Secundaria 2ª etapa  |  -.2910842   .1248737    -2.33   0.020    -.5360541   
> -.0461144
                 F.P.  |  -.1822383   .1247447    -1.46   0.144     -.426955   
>  .0624784
           Superiores  |  -.2136564   .1257698    -1.70   0.090    -.4603841   
>  .0330713
                       |
                 _cons |   .7287888   .1514973     4.81   0.000     .4315903   
>  1.025987
-------------------------------------------------------------------------------
---------

. est store pp_fe_controls

. regsave pp_dummy using 01_data/survey_data.dta, ci level(95) append addlabel 
> ///
> (Removed, Mun Size, Model, cabine_use, FE, Without region fixed effects)
(variable Removed was str8, now str19 to accommodate using data's values)
file 01_data/survey_data.dta saved

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured8_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Fake model to start the data
. regr pp_dummy CCAA

      Source |       SS           df       MS      Number of obs   =     3,376
-------------+----------------------------------   F(1, 3374)      =      0.01
       Model |  .001511648         1  .001511648   Prob > F        =    0.9221
    Residual |  533.401332     3,374  .158091681   R-squared       =    0.0000
-------------+----------------------------------   Adj R-squared   =   -0.0003
       Total |  533.402844     3,375  .158045287   Root MSE        =    .39761

------------------------------------------------------------------------------
    pp_dummy | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        CCAA |   .0001329   .0013588     0.10   0.922    -.0025313    .0027971
       _cons |   .1955201   .0137159    14.26   0.000     .1686279    .2224123
------------------------------------------------------------------------------

. regsave CCAA using 01_data/survey_data_2.dta, ci level(95) replace addlabel /
> //
> (Removed, fake, Model, fake,  FE, fake)
file 01_data/survey_data_2.dta saved

. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
(2,957 missing values generated)

. 
. * Actual analyses
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.income age age_s
> q i.education i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(44, 1311)       =       2.39
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0747
                                                Root MSE          =     .27993

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0160757   .0173974    -0.92   0.356    -.0
> 502054                                                                       
>            .018054
                       pp_dummy |  -.0348437   .0296604    -1.17   0.240    -.0
> 930307                                                                       
>           .0233433
            cabine_use_pp_dummy |   .1018081   .0460283     2.21   0.027     .0
> 115109                                                                       
>           .1921053
                                |
                         income |
         Menos o igual a 300 €  |   .0244379   .0642031     0.38   0.704    -.1
> 015141                                                                       
>             .15039
                De 301 a 600 €  |   .0761026   .0408352     1.86   0.063     -.
> 004007                                                                       
>           .1562122
                De 601 a 900 €  |   .0045225   .0306157     0.15   0.883    -.0
> 555387                                                                       
>           .0645837
              De 901 a 1.200 €  |   .0023769   .0280213     0.08   0.932    -.0
> 525945                                                                       
>           .0573483
            De 1.201 a 1.800 €  |  -.0079993   .0278846    -0.29   0.774    -.0
> 627027                                                                       
>           .0467041
            De 1.801 a 2.400 €  |   -.055555   .0301125    -1.84   0.065     -.
> 114629                                                                       
>            .003519
            De 2.401 a 3.000 €  |  -.0487728   .0420429    -1.16   0.246    -.1
> 312516                                                                       
>            .033706
            De 3.001 a 4.500 €  |   .0431181   .0667544     0.65   0.518    -.0
> 878389                                                                       
>           .1740751
            De 4.501 a 6.000 €  |  -.0901417   .0415935    -2.17   0.030    -.1
> 717388                                                                       
>          -.0085446
                Más de 6.000 €  |  -.0941105   .0439658    -2.14   0.032    -.1
> 803616                                                                       
>          -.0078595
                                |
                            age |  -.0004631   .0031208    -0.15   0.882    -.0
> 065855                                                                       
>           .0056592
                         age_sq |   .0000103   .0000331     0.31   0.755    -.0
> 000545                                                                       
>           .0000752
                                |
                      education |
                      Primaria  |  -.0846919   .0917369    -0.92   0.356     -.
> 264659                                                                       
>           .0952752
           Secundaria 1ª etapa  |  -.0476901   .0939749    -0.51   0.612    -.2
> 320477                                                                       
>           .1366675
           Secundaria 2ª etapa  |  -.0923449   .0943915    -0.98   0.328    -.2
> 775198                                                                       
>             .09283
                          F.P.  |   -.082031   .0938693    -0.87   0.382    -.2
> 661813                                                                       
>           .1021194
                    Superiores  |  -.0723339    .094541    -0.77   0.444    -.2
> 578021                                                                       
>           .1131344
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .057631   .0370509     1.56   0.120    -.0
> 150546                                                                       
>           .1303166
    10.001 a 50.000 habitantes  |   .0210893    .032618     0.65   0.518    -.0
> 428998                                                                       
>           .0850784
   50.001 a 100.000 habitantes  |   .0069832   .0375698     0.19   0.853    -.0
> 667204                                                                       
>           .0806868
  100.001 a 400.000 habitantes  |  -.0055116   .0337023    -0.16   0.870    -.0
> 716279                                                                       
>           .0606047
400.001 a 1.000.000 habitantes  |   -.038173    .036174    -1.06   0.292    -.1
> 091382                                                                       
>           .0327922
   Más de 1.000.000 habitantes  |  -.1006633   .0428258    -2.35   0.019     -.
> 184678                                                                       
>          -.0166487
                                |
                           CCAA |
                        Aragón  |  -.0182899   .0360452    -0.51   0.612    -.0
> 890024                                                                       
>           .0524226
      Asturias (Principado de)  |   .0557538    .054032     1.03   0.302    -.0
> 502449                                                                       
>           .1617525
               Balears (Illes)  |   .0565928   .0519132     1.09   0.276    -.0
> 452493                                                                       
>           .1584349
                      Canarias  |  -.0587738   .0344873    -1.70   0.089      -
> .12643                                                                       
>           .0088825
                     Cantabria  |   -.036857   .0364185    -1.01   0.312    -.1
> 083019                                                                       
>            .034588
            Castilla-La Mancha  |   .1270295   .0596927     2.13   0.034     .0
> 099259                                                                       
>           .2441332
               Castilla y León  |   .0857479   .0556374     1.54   0.124    -.0
> 234001                                                                       
>           .1948959
                      Cataluña  |   .0105907   .0350085     0.30   0.762    -.0
> 580881                                                                       
>           .0792695
          Comunitat Valenciana  |  -.0538111    .027652    -1.95   0.052    -.1
> 080581                                                                       
>           .0004359
                   Extremadura  |  -.0219642   .0431505    -0.51   0.611    -.1
> 066158                                                                       
>           .0626874
                       Galicia  |  -.0936278    .028606    -3.27   0.001    -.1
> 497464                                                                       
>          -.0375092
         Madrid (Comunidad de)  |   .0968967   .0415989     2.33   0.020      .
> 015289                                                                       
>           .1785043
            Murcia (Región de)  |   -.063292   .0247865    -2.55   0.011    -.1
> 119175                                                                       
>          -.0146664
  Navarra (Comunidad Foral de)  |  -.0200074   .0556981    -0.36   0.719    -.1
> 292747                                                                       
>           .0892598
                    País Vasco  |   -.059788   .0357435    -1.67   0.095    -.1
> 299088                                                                       
>           .0103327
                    Rioja (La)  |  -.0905551   .0255838    -3.54   0.000    -.1
> 407448                                                                       
>          -.0403655
    Ceuta (Ciudad Autónoma de)  |   .0942615   .0816352     1.15   0.248    -.0
> 658883                                                                       
>           .2544113
  Melilla (Ciudad Autónoma de)  |   -.034456   .0635353    -0.54   0.588    -.1
> 590981                                                                       
>            .090186
                                |
                          _cons |   .1584068   .1101955     1.44   0.151    -.0
> 577721                                                                       
>           .3745856
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Female, Model, uncomfortable, FE, With region fixed effects)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female age age_sq 
> i.education i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,845
                                                F(35, 1808)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0659
                                                Root MSE          =     .29604

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |    -.02596   .0166925    -1.56   0.120    -.0
> 586987                                                                       
>           .0067787
                       pp_dummy |  -.0321446   .0268523    -1.20   0.231    -.0
> 848094                                                                       
>           .0205203
            cabine_use_pp_dummy |   .0997502    .041755     2.39   0.017     .0
> 178572                                                                       
>           .1816432
                         female |   .0244014    .013965     1.75   0.081    -.0
> 029877                                                                       
>           .0517905
                            age |   .0017546   .0025987     0.68   0.500    -.0
> 033421                                                                       
>           .0068514
                         age_sq |  -.0000189   .0000281    -0.67   0.501     -.
> 000074                                                                       
>           .0000362
                                |
                      education |
                      Primaria  |  -.1559313   .0792874    -1.97   0.049    -.3
> 114358                                                                       
>          -.0004268
           Secundaria 1ª etapa  |  -.1799854   .0797898    -2.26   0.024    -.3
> 364753                                                                       
>          -.0234955
           Secundaria 2ª etapa  |  -.1991584   .0800952    -2.49   0.013    -.3
> 562473                                                                       
>          -.0420695
                          F.P.  |  -.1877586   .0801219    -2.34   0.019    -.3
> 448997                                                                       
>          -.0306174
                    Superiores  |  -.2034999   .0794906    -2.56   0.011    -.3
> 594031                                                                       
>          -.0475968
                         Otros  |   .7543421   .0844704     8.93   0.000     .5
> 886723                                                                       
>            .920012
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0519357   .0339977     1.53   0.127    -.0
> 147431                                                                       
>           .1186145
    10.001 a 50.000 habitantes  |   .0332507   .0299087     1.11   0.266    -.0
> 254085                                                                       
>           .0919099
   50.001 a 100.000 habitantes  |   .0341557   .0347578     0.98   0.326     -.
> 034014                                                                       
>           .1023254
  100.001 a 400.000 habitantes  |   .0086743   .0310895     0.28   0.780    -.0
> 523008                                                                       
>           .0696493
400.001 a 1.000.000 habitantes  |  -.0335382   .0326885    -1.03   0.305    -.0
> 976495                                                                       
>            .030573
   Más de 1.000.000 habitantes  |  -.0816202   .0362992    -2.25   0.025    -.1
> 528129                                                                       
>          -.0104274
                                |
                           CCAA |
                        Aragón  |   .0046845   .0392841     0.12   0.905    -.0
> 723624                                                                       
>           .0817314
      Asturias (Principado de)  |   .0869444   .0560895     1.55   0.121    -.0
> 230628                                                                       
>           .1969515
               Balears (Illes)  |   .0294812   .0426592     0.69   0.490    -.0
> 541854                                                                       
>           .1131478
                      Canarias  |  -.0674888   .0354478    -1.90   0.057    -.1
> 370117                                                                       
>            .002034
                     Cantabria  |  -.0269234   .0386741    -0.70   0.486     -.
> 102774                                                                       
>           .0489272
            Castilla-La Mancha  |   .1236697   .0584612     2.12   0.035      .
> 009011                                                                       
>           .2383284
               Castilla y León  |   .0958419    .050632     1.89   0.059    -.0
> 034614                                                                       
>           .1951453
                      Cataluña  |  -.0403136   .0282889    -1.43   0.154     -.
> 095796                                                                       
>           .0151688
          Comunitat Valenciana  |  -.0759636   .0250698    -3.03   0.002    -.1
> 251324                                                                       
>          -.0267948
                   Extremadura  |  -.0248094   .0404769    -0.61   0.540    -.1
> 041959                                                                       
>            .054577
                       Galicia  |  -.0574159   .0344846    -1.66   0.096    -.1
> 250498                                                                       
>            .010218
         Madrid (Comunidad de)  |   .0469842   .0363192     1.29   0.196    -.0
> 242477                                                                       
>           .1182161
            Murcia (Región de)  |  -.0891789   .0230362    -3.87   0.000    -.1
> 343592                                                                       
>          -.0439985
  Navarra (Comunidad Foral de)  |   .0296059   .0604033     0.49   0.624    -.0
> 888618                                                                       
>           .1480736
                    País Vasco  |  -.0757668   .0323512    -2.34   0.019    -.1
> 392164                                                                       
>          -.0123172
                    Rioja (La)  |  -.0249346   .0413643    -0.60   0.547    -.1
> 060614                                                                       
>           .0561923
    Ceuta (Ciudad Autónoma de)  |   .0504117   .0700348     0.72   0.472    -.0
> 869459                                                                       
>           .1877694
  Melilla (Ciudad Autónoma de)  |  -.0710757    .065662    -1.08   0.279    -.1
> 998571                                                                       
>           .0577057
                                |
                          _cons |   .2420786   .0968857     2.50   0.013     .0
> 520588                                                                       
>           .4320984
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Income, Model, uncomfortable, FE, With region fixed effects)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.
> education i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(43, 1312)       =       2.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0763
                                                Root MSE          =     .27958

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0171238   .0173984    -0.98   0.325    -.0
> 512555                                                                       
>            .017008
                       pp_dummy |  -.0382663   .0291772    -1.31   0.190    -.0
> 955054                                                                       
>           .0189729
            cabine_use_pp_dummy |   .1078883   .0460072     2.35   0.019     .0
> 176326                                                                       
>            .198144
                         female |   .0290755   .0156643     1.86   0.064    -.0
> 016542                                                                       
>           .0598052
                                |
                         income |
         Menos o igual a 300 €  |   .0257561   .0635193     0.41   0.685    -.0
> 988543                                                                       
>           .1503666
                De 301 a 600 €  |   .0814072   .0401394     2.03   0.043     .0
> 026628                                                                       
>           .1601516
                De 601 a 900 €  |   .0116792   .0291994     0.40   0.689    -.0
> 456033                                                                       
>           .0689617
              De 901 a 1.200 €  |   .0119859   .0255522     0.47   0.639    -.0
> 381419                                                                       
>           .0621136
            De 1.201 a 1.800 €  |   .0074195   .0246294     0.30   0.763    -.0
> 408978                                                                       
>           .0557367
            De 1.801 a 2.400 €  |  -.0345489   .0259456    -1.33   0.183    -.0
> 854483                                                                       
>           .0163504
            De 2.401 a 3.000 €  |  -.0234597   .0378318    -0.62   0.535    -.0
> 976773                                                                       
>           .0507578
            De 3.001 a 4.500 €  |   .0631557   .0661511     0.95   0.340    -.0
> 666177                                                                       
>           .1929291
            De 4.501 a 6.000 €  |  -.0752633   .0467788    -1.61   0.108    -.1
> 670327                                                                       
>           .0165062
                Más de 6.000 €  |  -.0686962    .040677    -1.69   0.091    -.1
> 484952                                                                       
>           .0111029
                                |
                      education |
                      Primaria  |  -.0879912   .0913813    -0.96   0.336    -.2
> 672607                                                                       
>           .0912783
           Secundaria 1ª etapa  |  -.0613412   .0915489    -0.67   0.503    -.2
> 409394                                                                       
>            .118257
           Secundaria 2ª etapa  |  -.1086507   .0916907    -1.18   0.236    -.2
> 885272                                                                       
>           .0712257
                          F.P.  |  -.0997864   .0908392    -1.10   0.272    -.2
> 779923                                                                       
>           .0784195
                    Superiores  |  -.0948682   .0917026    -1.03   0.301    -.2
> 747679                                                                       
>           .0850315
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0541246   .0368802     1.47   0.142    -.0
> 182261                                                                       
>           .1264752
    10.001 a 50.000 habitantes  |    .019289   .0322746     0.60   0.550    -.0
> 440265                                                                       
>           .0826045
   50.001 a 100.000 habitantes  |   .0052083   .0375743     0.14   0.890    -.0
> 685039                                                                       
>           .0789205
  100.001 a 400.000 habitantes  |  -.0070772   .0337276    -0.21   0.834    -.0
> 732431                                                                       
>           .0590886
400.001 a 1.000.000 habitantes  |  -.0377464   .0357858    -1.05   0.292      -
> .10795                                                                       
>           .0324572
   Más de 1.000.000 habitantes  |  -.1036478   .0421054    -2.46   0.014    -.1
> 862491                                                                       
>          -.0210465
                                |
                           CCAA |
                        Aragón  |   -.021064   .0353831    -0.60   0.552    -.0
> 904775                                                                       
>           .0483496
      Asturias (Principado de)  |   .0560403    .054163     1.03   0.301    -.0
> 502153                                                                       
>           .1622959
               Balears (Illes)  |   .0524065   .0516936     1.01   0.311    -.0
> 490046                                                                       
>           .1538175
                      Canarias  |  -.0630433   .0343871    -1.83   0.067    -.1
> 305029                                                                       
>           .0044163
                     Cantabria  |  -.0339612    .036313    -0.94   0.350    -.1
> 051991                                                                       
>           .0372768
            Castilla-La Mancha  |   .1272402   .0595519     2.14   0.033     .0
> 104128                                                                       
>           .2440676
               Castilla y León  |   .0865629   .0550842     1.57   0.116    -.0
> 214999                                                                       
>           .1946257
                      Cataluña  |   .0096528   .0353444     0.27   0.785     -.
> 059685                                                                       
>           .0789906
          Comunitat Valenciana  |  -.0535107   .0273373    -1.96   0.051    -.1
> 071404                                                                       
>            .000119
                   Extremadura  |  -.0204161   .0432372    -0.47   0.637    -.1
> 052377                                                                       
>           .0644056
                       Galicia  |  -.0907454   .0279328    -3.25   0.001    -.1
> 455432                                                                       
>          -.0359476
         Madrid (Comunidad de)  |   .0986689   .0413767     2.38   0.017     .0
> 174972                                                                       
>           .1798407
            Murcia (Región de)  |  -.0642349   .0246997    -2.60   0.009    -.1
> 126902                                                                       
>          -.0157796
  Navarra (Comunidad Foral de)  |  -.0140547   .0555841    -0.25   0.800    -.1
> 230981                                                                       
>           .0949887
                    País Vasco  |  -.0579101    .035502    -1.63   0.103    -.1
> 275569                                                                       
>           .0117367
                    Rioja (La)  |  -.0900179   .0255234    -3.53   0.000     -.
> 140089                                                                       
>          -.0399469
    Ceuta (Ciudad Autónoma de)  |   .0966838   .0806248     1.20   0.231    -.0
> 614839                                                                       
>           .2548514
  Melilla (Ciudad Autónoma de)  |  -.0332477   .0640349    -0.52   0.604    -.1
> 588697                                                                       
>           .0923742
                                |
                          _cons |   .1548695   .0964842     1.61   0.109    -.0
> 344107                                                                       
>           .3441497
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Age and age squared, Model, uncomfortable, FE, With region fixed ef
> fects)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income ag
> e age_sq i.TAMUNI i.CCAA, r

Linear regression                               Number of obs     =      1,357
                                                F(40, 1316)       =       2.62
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0727
                                                Root MSE          =     .27971

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0148612   .0173116    -0.86   0.391    -.0
> 488225                                                                       
>           .0191001
                       pp_dummy |  -.0373887   .0297172    -1.26   0.209    -.0
> 956871                                                                       
>           .0209096
            cabine_use_pp_dummy |   .1023232   .0459078     2.23   0.026     .0
> 122627                                                                       
>           .1923836
                         female |   .0275267   .0155344     1.77   0.077    -.0
> 029483                                                                       
>           .0580016
                                |
                         income |
         Menos o igual a 300 €  |   .0287215   .0631973     0.45   0.650     -.
> 095257                                                                       
>              .1527
                De 301 a 600 €  |   .0805202   .0408338     1.97   0.049     .0
> 004138                                                                       
>           .1606266
                De 601 a 900 €  |   .0115008    .029934     0.38   0.701    -.0
> 472229                                                                       
>           .0702244
              De 901 a 1.200 €  |   .0123277   .0283916     0.43   0.664    -.0
> 433701                                                                       
>           .0680255
            De 1.201 a 1.800 €  |   .0030491   .0279887     0.11   0.913    -.0
> 518582                                                                       
>           .0579565
            De 1.801 a 2.400 €  |  -.0451732   .0280957    -1.61   0.108    -.1
> 002905                                                                       
>            .009944
            De 2.401 a 3.000 €  |  -.0331929   .0404812    -0.82   0.412    -.1
> 126076                                                                       
>           .0462219
            De 3.001 a 4.500 €  |   .0577207   .0657477     0.88   0.380     -.
> 071261                                                                       
>           .1867024
            De 4.501 a 6.000 €  |   -.083732   .0423313    -1.98   0.048    -.1
> 667762                                                                       
>          -.0006879
                Más de 6.000 €  |   -.082443   .0400923    -2.06   0.040    -.1
> 610948                                                                       
>          -.0037913
                                |
                            age |  -.0007594   .0030641    -0.25   0.804    -.0
> 067705                                                                       
>           .0052517
                         age_sq |   .0000143   .0000317     0.45   0.653    -.0
> 000479                                                                       
>           .0000764
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0533775   .0372372     1.43   0.152    -.0
> 196733                                                                       
>           .1264283
    10.001 a 50.000 habitantes  |    .020365    .033162     0.61   0.539    -.0
> 446912                                                                       
>           .0854211
   50.001 a 100.000 habitantes  |   .0012267   .0378852     0.03   0.974    -.0
> 730952                                                                       
>           .0755486
  100.001 a 400.000 habitantes  |  -.0091166   .0338217    -0.27   0.788    -.0
> 754669                                                                       
>           .0572338
400.001 a 1.000.000 habitantes  |  -.0444173   .0360444    -1.23   0.218    -.1
> 151281                                                                       
>           .0262936
   Más de 1.000.000 habitantes  |   -.103267   .0422757    -2.44   0.015    -.1
> 862022                                                                       
>          -.0203319
                                |
                           CCAA |
                        Aragón  |  -.0278589   .0353843    -0.79   0.431    -.0
> 972747                                                                       
>            .041557
      Asturias (Principado de)  |   .0538211   .0546345     0.99   0.325    -.0
> 533591                                                                       
>           .1610013
               Balears (Illes)  |   .0494898   .0515622     0.96   0.337    -.0
> 516632                                                                       
>           .1506429
                      Canarias  |   -.069039   .0341656    -2.02   0.044    -.1
> 360641                                                                       
>          -.0020139
                     Cantabria  |  -.0431382    .036654    -1.18   0.239    -.1
> 150448                                                                       
>           .0287684
            Castilla-La Mancha  |   .1220683     .05893     2.07   0.039     .0
> 064613                                                                       
>           .2376752
               Castilla y León  |    .076623   .0554462     1.38   0.167    -.0
> 321496                                                                       
>           .1853956
                      Cataluña  |   .0050742    .035092     0.14   0.885     -.
> 063768                                                                       
>           .0739165
          Comunitat Valenciana  |  -.0583847   .0272144    -2.15   0.032    -.1
> 117729                                                                       
>          -.0049964
                   Extremadura  |  -.0227128   .0428016    -0.53   0.596    -.1
> 066795                                                                       
>            .061254
                       Galicia  |  -.0982743   .0284998    -3.45   0.001    -.1
> 541843                                                                       
>          -.0423642
         Madrid (Comunidad de)  |   .0904505   .0413352     2.19   0.029     .0
> 093604                                                                       
>           .1715407
            Murcia (Región de)  |  -.0673089   .0247001    -2.73   0.007    -.1
> 157648                                                                       
>          -.0188531
  Navarra (Comunidad Foral de)  |  -.0218557   .0552232    -0.40   0.692    -.1
> 301909                                                                       
>           .0864795
                    País Vasco  |   -.066178   .0348013    -1.90   0.057    -.1
> 344501                                                                       
>           .0020941
                    Rioja (La)  |  -.0962578   .0249472    -3.86   0.000    -.1
> 451984                                                                       
>          -.0473173
    Ceuta (Ciudad Autónoma de)  |   .0962133   .0810814     1.19   0.236    -.0
> 628495                                                                       
>           .2552762
  Melilla (Ciudad Autónoma de)  |  -.0347795   .0634464    -0.55   0.584    -.1
> 592467                                                                       
>           .0896877
                                |
                          _cons |   .0760915   .0753512     1.01   0.313      -
> .07173                                                                       
>           .2239131
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Education, Model, uncomfortable, FE, With region fixed effects)
(variable Removed was str9, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income ag
> e age_sq i.education i.CCAA, r

Linear regression                               Number of obs     =      1,356
                                                F(39, 1316)       =       2.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0634
                                                Root MSE          =     .28109

-------------------------------------------------------------------------------
----------------
                              |               Robust
                uncomfortable | Coefficient  std. err.      t    P>|t|     [95%
>  con                                                                         
>     f. interval]
------------------------------+------------------------------------------------
----------------
                   cabine_use |  -.0046278    .017142    -0.27   0.787    -.038
> 2565                                                                         
>         .0290009
                     pp_dummy |  -.0468004   .0303969    -1.54   0.124    -.106
> 4321                                                                         
>         .0128313
          cabine_use_pp_dummy |    .117398   .0461072     2.55   0.011     .026
> 9463                                                                         
>         .2078496
                       female |   .0284169   .0158636     1.79   0.073    -.002
> 7038                                                                         
>         .0595377
                              |
                       income |
       Menos o igual a 300 €  |   .0221153   .0643666     0.34   0.731     -.10
> 4157                                                                         
>         .1483875
              De 301 a 600 €  |   .0819267   .0410386     2.00   0.046     .001
> 4185                                                                         
>          .162435
              De 601 a 900 €  |   .0068138   .0305488     0.22   0.824     -.05
> 3116                                                                         
>         .0667435
            De 901 a 1.200 €  |   .0078883   .0283493     0.28   0.781    -.047
> 7264                                                                         
>          .063503
          De 1.201 a 1.800 €  |   .0018073   .0281908     0.06   0.949    -.053
> 4964                                                                         
>         .0571111
          De 1.801 a 2.400 €  |  -.0354991   .0303806    -1.17   0.243    -.095
> 0987                                                                         
>         .0241006
          De 2.401 a 3.000 €  |  -.0374976   .0430184    -0.87   0.384    -.121
> 8897                                                                         
>         .0468945
          De 3.001 a 4.500 €  |   .0552316   .0699756     0.79   0.430    -.082
> 0443                                                                         
>         .1925075
          De 4.501 a 6.000 €  |  -.0609208   .0386488    -1.58   0.115    -.136
> 7408                                                                         
>         .0148991
              Más de 6.000 €  |  -.0513082   .0329827    -1.56   0.120    -.116
> 0126                                                                         
>         .0133961
                              |
                          age |  -.0014073   .0031425    -0.45   0.654    -.007
> 5721                                                                         
>         .0047576
                       age_sq |   .0000163   .0000333     0.49   0.625    -.000
> 0491                                                                         
>         .0000817
                              |
                    education |
                    Primaria  |  -.0851615   .0917651    -0.93   0.354    -.265
> 1834                                                                         
>         .0948603
         Secundaria 1ª etapa  |   -.048432   .0937855    -0.52   0.606    -.232
> 4174                                                                         
>         .1355533
         Secundaria 2ª etapa  |   -.095617   .0938743    -1.02   0.309    -.279
> 7765                                                                         
>         .0885426
                        F.P.  |  -.0879323    .093448    -0.94   0.347    -.271
> 2557                                                                         
>         .0953911
                  Superiores  |  -.0886979   .0939451    -0.94   0.345    -.272
> 9965                                                                         
>         .0956007
                              |
                         CCAA |
                      Aragón  |  -.0358066   .0356851    -1.00   0.316    -.105
> 8124                                                                         
>         .0341992
    Asturias (Principado de)  |   .0571556   .0529941     1.08   0.281    -.046
> 8066                                                                         
>         .1611177
             Balears (Illes)  |   .0423877   .0506476     0.84   0.403    -.056
> 9712                                                                         
>         .1417465
                    Canarias  |  -.0666758   .0334143    -2.00   0.046    -.132
> 2269                                                                         
>        -.0011246
                   Cantabria  |   -.020706   .0347234    -0.60   0.551    -.088
> 8253                                                                         
>         .0474134
          Castilla-La Mancha  |   .1367653   .0589115     2.32   0.020     .021
> 1946                                                                         
>          .252336
             Castilla y León  |    .089748   .0550609     1.63   0.103    -.018
> 2686                                                                         
>         .1977647
                    Cataluña  |  -.0095527   .0314368    -0.30   0.761    -.071
> 2245                                                                         
>         .0521191
        Comunitat Valenciana  |  -.0533871    .027254    -1.96   0.050    -.106
> 8531                                                                         
>         .0000789
                 Extremadura  |  -.0149694   .0426013    -0.35   0.725    -.098
> 5433                                                                         
>         .0686046
                     Galicia  |  -.0780152   .0264908    -2.94   0.003     -.12
> 9984                                                                         
>        -.0260465
       Madrid (Comunidad de)  |   .0688537   .0359927     1.91   0.056    -.001
> 7555                                                                         
>          .139463
          Murcia (Región de)  |  -.0750808   .0251553    -2.98   0.003    -.124
> 4297                                                                         
>        -.0257319
Navarra (Comunidad Foral de)  |   .0079504   .0539997     0.15   0.883    -.097
> 9844                                                                         
>         .1138853
                  País Vasco  |  -.0542921   .0351403    -1.55   0.123    -.123
> 2292                                                                         
>          .014645
                  Rioja (La)  |  -.0914643   .0228617    -4.00   0.000    -.136
> 3136                                                                         
>         -.046615
  Ceuta (Ciudad Autónoma de)  |   .0865314   .0781882     1.11   0.269    -.066
> 8557                                                                         
>         .2399186
Melilla (Ciudad Autónoma de)  |  -.0386532   .0611644    -0.63   0.528    -.158
> 6435                                                                         
>         .0813371
                              |
                        _cons |   .1760432   .1064255     1.65   0.098    -.032
> 7391                                                                         
>         .3848254
-------------------------------------------------------------------------------
----------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Mun Size, Model, uncomfortable, FE, With region fixed effects)
(variable Removed was str8, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy i.income age age_s
> q i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,356
                                                F(26, 1329)       =       4.89
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0345
                                                Root MSE          =     .28401

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0335483   .0167101    -2.01   0.045    -.0
> 663293                                                                       
>          -.0007673
                       pp_dummy |   -.032705   .0298347    -1.10   0.273    -.0
> 912333                                                                       
>           .0258233
            cabine_use_pp_dummy |   .1125013   .0480388     2.34   0.019     .0
> 182611                                                                       
>           .2067415
                                |
                         income |
         Menos o igual a 300 €  |   .0292243   .0640083     0.46   0.648    -.0
> 963439                                                                       
>           .1547925
                De 301 a 600 €  |   .0631157   .0416106     1.52   0.130    -.0
> 185138                                                                       
>           .1447453
                De 601 a 900 €  |   .0005856   .0309611     0.02   0.985    -.0
> 601524                                                                       
>           .0613235
              De 901 a 1.200 €  |   .0048339   .0290146     0.17   0.868    -.0
> 520856                                                                       
>           .0617533
            De 1.201 a 1.800 €  |  -.0026074   .0277713    -0.09   0.925    -.0
> 570878                                                                       
>            .051873
            De 1.801 a 2.400 €  |  -.0544109   .0294214    -1.85   0.065    -.1
> 121283                                                                       
>           .0033064
            De 2.401 a 3.000 €  |  -.0371614   .0423932    -0.88   0.381    -.1
> 203264                                                                       
>           .0460035
            De 3.001 a 4.500 €  |   .0480765   .0703213     0.68   0.494    -.0
> 898763                                                                       
>           .1860293
            De 4.501 a 6.000 €  |  -.0984699   .0310148    -3.17   0.002    -.1
> 593132                                                                       
>          -.0376267
                Más de 6.000 €  |  -.0918733    .034138    -2.69   0.007    -.1
> 588434                                                                       
>          -.0249031
                                |
                            age |  -.0014949    .003149    -0.47   0.635    -.0
> 076723                                                                       
>           .0046826
                         age_sq |   .0000197   .0000333     0.59   0.555    -.0
> 000457                                                                       
>            .000085
                                |
                      education |
                      Primaria  |  -.0908718   .0899843    -1.01   0.313    -.2
> 673985                                                                       
>           .0856549
           Secundaria 1ª etapa  |   -.055418    .091148    -0.61   0.543    -.2
> 342277                                                                       
>           .1233916
           Secundaria 2ª etapa  |  -.0999778   .0915458    -1.09   0.275    -.2
> 795678                                                                       
>           .0796121
                          F.P.  |  -.0925209   .0911118    -1.02   0.310    -.2
> 712596                                                                       
>           .0862178
                    Superiores  |  -.0820517   .0915368    -0.90   0.370    -.2
> 616241                                                                       
>           .0975208
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0625432   .0376296     1.66   0.097    -.0
> 112767                                                                       
>            .136363
    10.001 a 50.000 habitantes  |   .0189713   .0325457     0.58   0.560    -.0
> 448753                                                                       
>           .0828178
   50.001 a 100.000 habitantes  |   .0379784   .0365266     1.04   0.299    -.0
> 336776                                                                       
>           .1096344
  100.001 a 400.000 habitantes  |   .0055404   .0327895     0.17   0.866    -.0
> 587844                                                                       
>           .0698651
400.001 a 1.000.000 habitantes  |  -.0481135   .0323246    -1.49   0.137    -.1
> 115263                                                                       
>           .0152994
   Más de 1.000.000 habitantes  |  -.0417802    .036328    -1.15   0.250    -.1
> 130467                                                                       
>           .0294863
                                |
                          _cons |   .1931122   .1070824     1.80   0.072    -.0
> 169568                                                                       
>           .4031811
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Female, Model, uncomfortable, FE, Without region fixed effects)
(variable Removed was str6, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female age age_sq 
> i.education i.TAMUNI, r

Linear regression                               Number of obs     =      1,845
                                                F(17, 1826)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0343
                                                Root MSE          =     .29953

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0295945   .0154625    -1.91   0.056    -.0
> 599206                                                                       
>           .0007316
                       pp_dummy |  -.0179845   .0266268    -0.68   0.499    -.0
> 702067                                                                       
>           .0342378
            cabine_use_pp_dummy |   .0952435   .0426052     2.24   0.026     .0
> 116835                                                                       
>           .1788035
                         female |   .0226491   .0142247     1.59   0.112    -.0
> 052493                                                                       
>           .0505474
                            age |   .0016713   .0025975     0.64   0.520    -.0
> 034231                                                                       
>           .0067657
                         age_sq |  -.0000195    .000028    -0.70   0.486    -.0
> 000744                                                                       
>           .0000354
                                |
                      education |
                      Primaria  |  -.1621373   .0793387    -2.04   0.041    -.3
> 177415                                                                       
>          -.0065332
           Secundaria 1ª etapa  |  -.1912991   .0786957    -2.43   0.015    -.3
> 456422                                                                       
>           -.036956
           Secundaria 2ª etapa  |  -.2090412   .0790242    -2.65   0.008    -.3
> 640285                                                                       
>          -.0540538
                          F.P.  |   -.201864   .0790355    -2.55   0.011    -.3
> 568735                                                                       
>          -.0468545
                    Superiores  |  -.2133883   .0784253    -2.72   0.007    -.3
> 672011                                                                       
>          -.0595756
                         Otros  |   .6955513   .0788611     8.82   0.000     .5
> 408838                                                                       
>           .8502188
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0456746   .0344501     1.33   0.185    -.0
> 218911                                                                       
>           .1132403
    10.001 a 50.000 habitantes  |   .0162852   .0300945     0.54   0.588    -.0
> 427381                                                                       
>           .0753084
   50.001 a 100.000 habitantes  |   .0407846   .0342481     1.19   0.234    -.0
> 263851                                                                       
>           .1079542
  100.001 a 400.000 habitantes  |   .0013441    .030581     0.04   0.965    -.0
> 586332                                                                       
>           .0613215
400.001 a 1.000.000 habitantes  |  -.0537974   .0307416    -1.75   0.080    -.1
> 140897                                                                       
>            .006495
   Más de 1.000.000 habitantes  |  -.0690306   .0311348    -2.22   0.027    -.1
> 300942                                                                       
>           -.007967
                                |
                          _cons |   .2597643   .0950502     2.73   0.006     .0
> 733458                                                                       
>           .4461829
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Income, Model, uncomfortable, FE, Without region fixed effects)
(variable Removed was str6, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income i.
> education i.TAMUNI, r

Linear regression                               Number of obs     =      1,356
                                                F(25, 1330)       =       2.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0360
                                                Root MSE          =     .28367

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0345646   .0166902    -2.07   0.039    -.0
> 673066                                                                       
>          -.0018226
                       pp_dummy |  -.0365715   .0291593    -1.25   0.210    -.0
> 937748                                                                       
>           .0206318
            cabine_use_pp_dummy |   .1177871    .048027     2.45   0.014       
> .02357                                                                       
>           .2120041
                         female |    .028316   .0158684     1.78   0.075    -.0
> 028138                                                                       
>           .0594458
                                |
                         income |
         Menos o igual a 300 €  |   .0289619   .0633741     0.46   0.648    -.0
> 953622                                                                       
>            .153286
                De 301 a 600 €  |   .0654802   .0407089     1.61   0.108    -.0
> 143805                                                                       
>           .1453409
                De 601 a 900 €  |   .0048702   .0294306     0.17   0.869    -.0
> 528652                                                                       
>           .0626056
              De 901 a 1.200 €  |   .0109067   .0265652     0.41   0.681    -.0
> 412075                                                                       
>            .063021
            De 1.201 a 1.800 €  |    .008148   .0243824     0.33   0.738    -.0
> 396842                                                                       
>           .0559802
            De 1.801 a 2.400 €  |  -.0391416    .024995    -1.57   0.118    -.0
> 881755                                                                       
>           .0098924
            De 2.401 a 3.000 €  |  -.0177987   .0380488    -0.47   0.640    -.0
> 924408                                                                       
>           .0568435
            De 3.001 a 4.500 €  |   .0631101   .0693773     0.91   0.363    -.0
> 729907                                                                       
>           .1992109
            De 4.501 a 6.000 €  |  -.0892269   .0314683    -2.84   0.005    -.1
> 509599                                                                       
>          -.0274939
                Más de 6.000 €  |  -.0727006   .0300055    -2.42   0.016    -.1
> 315638                                                                       
>          -.0138375
                                |
                      education |
                      Primaria  |  -.0949011   .0896831    -1.06   0.290    -.2
> 708368                                                                       
>           .0810347
           Secundaria 1ª etapa  |  -.0694944   .0891665    -0.78   0.436    -.2
> 444168                                                                       
>           .1054279
           Secundaria 2ª etapa  |   -.115004   .0893219    -1.29   0.198    -.2
> 902312                                                                       
>           .0602232
                          F.P.  |  -.1096161    .088635    -1.24   0.216    -.2
> 834958                                                                       
>           .0642636
                    Superiores  |  -.1032968   .0892688    -1.16   0.247    -.2
> 784198                                                                       
>           .0718262
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .060967     .03755     1.62   0.105    -.0
> 126967                                                                       
>           .1346307
    10.001 a 50.000 habitantes  |   .0180663   .0322667     0.56   0.576    -.0
> 452329                                                                       
>           .0813654
   50.001 a 100.000 habitantes  |    .037454   .0364719     1.03   0.305    -.0
> 340947                                                                       
>           .1090027
  100.001 a 400.000 habitantes  |   .0042394   .0328795     0.13   0.897    -.0
> 602619                                                                       
>           .0687407
400.001 a 1.000.000 habitantes  |  -.0487448   .0320161    -1.52   0.128    -.1
> 115525                                                                       
>           .0140628
   Más de 1.000.000 habitantes  |  -.0435309   .0356015    -1.22   0.222    -.1
> 133721                                                                       
>           .0263104
                                |
                          _cons |   .1672128   .0925174     1.81   0.071    -.0
> 142831                                                                       
>           .3487088
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Age and age squared, Model, uncomfortable, FE, Without region fixed
>  effects)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income ag
> e age_sq i.TAMUNI, r

Linear regression                               Number of obs     =      1,357
                                                F(22, 1334)       =       3.55
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0325
                                                Root MSE          =     .28378

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0322626   .0165816    -1.95   0.052    -.0
> 647914                                                                       
>           .0002663
                       pp_dummy |  -.0352912    .029807    -1.18   0.237    -.0
> 937648                                                                       
>           .0231824
            cabine_use_pp_dummy |   .1135781   .0478575     2.37   0.018      .
> 019694                                                                       
>           .2074622
                         female |   .0274832   .0157701     1.74   0.082    -.0
> 034537                                                                       
>           .0584201
                                |
                         income |
         Menos o igual a 300 €  |   .0331502   .0627237     0.53   0.597    -.0
> 898976                                                                       
>           .1561979
                De 301 a 600 €  |   .0673569   .0416342     1.62   0.106    -.0
> 143187                                                                       
>           .1490324
                De 601 a 900 €  |   .0071364   .0302098     0.24   0.813    -.0
> 521276                                                                       
>           .0664003
              De 901 a 1.200 €  |   .0135615   .0294519     0.46   0.645    -.0
> 442156                                                                       
>           .0713387
            De 1.201 a 1.800 €  |   .0066919   .0279957     0.24   0.811    -.0
> 482284                                                                       
>           .0616122
            De 1.801 a 2.400 €  |  -.0456178   .0276663    -1.65   0.099     -.
> 099892                                                                       
>           .0086565
            De 2.401 a 3.000 €  |  -.0237488     .04087    -0.58   0.561    -.1
> 039252                                                                       
>           .0564277
            De 3.001 a 4.500 €  |   .0603227   .0689062     0.88   0.381    -.0
> 748535                                                                       
>            .195499
            De 4.501 a 6.000 €  |  -.0927065   .0297194    -3.12   0.002    -.1
> 510083                                                                       
>          -.0344046
                Más de 6.000 €  |  -.0842078    .031523    -2.67   0.008    -.1
> 460479                                                                       
>          -.0223677
                                |
                            age |  -.0017978   .0031266    -0.57   0.565    -.0
> 079314                                                                       
>           .0043359
                         age_sq |   .0000241   .0000324     0.75   0.456    -.0
> 000394                                                                       
>           .0000877
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0599233   .0378521     1.58   0.114    -.0
> 143328                                                                       
>           .1341794
    10.001 a 50.000 habitantes  |   .0190365   .0331722     0.57   0.566    -.0
> 460389                                                                       
>           .0841118
   50.001 a 100.000 habitantes  |   .0342488   .0369282     0.93   0.354    -.0
> 381949                                                                       
>           .1066925
  100.001 a 400.000 habitantes  |   .0023511   .0329244     0.07   0.943    -.0
> 622381                                                                       
>           .0669403
400.001 a 1.000.000 habitantes  |  -.0538814   .0323453    -1.67   0.096    -.1
> 173345                                                                       
>           .0095718
   Más de 1.000.000 habitantes  |  -.0453626   .0358896    -1.26   0.206    -.1
> 157688                                                                       
>           .0250437
                                |
                          _cons |   .0969928   .0719354     1.35   0.178    -.0
> 441261                                                                       
>           .2381117
-------------------------------------------------------------------------------
------------------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Education, Model, uncomfortable, FE, Without region fixed effects)
(variable Removed was str9, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
. regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female i.income ag
> e age_sq i.education, r

Linear regression                               Number of obs     =      1,356
                                                F(21, 1334)       =       4.41
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0247
                                                Root MSE          =     .28491

-------------------------------------------------------------------------------
---------
                       |               Robust
         uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. 
> interval]
-----------------------+-------------------------------------------------------
---------
            cabine_use |  -.0189155    .016494    -1.15   0.252    -.0512725   
>  .0134415
              pp_dummy |  -.0401891   .0300956    -1.34   0.182     -.099229   
>  .0188508
   cabine_use_pp_dummy |   .1257105   .0477886     2.63   0.009     .0319616   
>  .2194595
                female |   .0279576   .0160518     1.74   0.082     -.003532   
>  .0594471
                       |
                income |
Menos o igual a 300 €  |   .0238241   .0637905     0.37   0.709    -.1013164   
>  .1489647
       De 301 a 600 €  |   .0686293   .0417296     1.64   0.100    -.0132334   
>  .1504921
       De 601 a 900 €  |   .0012665    .030778     0.04   0.967     -.059112   
>   .061645
     De 901 a 1.200 €  |   .0082246   .0291872     0.28   0.778    -.0490333   
>  .0654825
   De 1.201 a 1.800 €  |    .005395   .0279205     0.19   0.847    -.0493777   
>  .0601678
   De 1.801 a 2.400 €  |  -.0374543   .0291452    -1.29   0.199    -.0946297   
>   .019721
   De 2.401 a 3.000 €  |  -.0274802   .0424847    -0.65   0.518    -.1108244   
>   .055864
   De 3.001 a 4.500 €  |   .0551094   .0710493     0.78   0.438     -.084271   
>  .1944898
   De 4.501 a 6.000 €  |  -.0796096   .0316605    -2.51   0.012    -.1417193   
> -.0174999
       Más de 6.000 €  |  -.0535342   .0275653    -1.94   0.052    -.1076102   
>  .0005419
                       |
                   age |  -.0022354    .003146    -0.71   0.477    -.0084071   
>  .0039363
                age_sq |   .0000242   .0000333     0.73   0.467    -.0000411   
>  .0000895
                       |
             education |
             Primaria  |  -.0935315   .0906993    -1.03   0.303    -.2714603   
>  .0843973
  Secundaria 1ª etapa  |  -.0577573   .0915041    -0.63   0.528    -.2372649   
>  .1217504
  Secundaria 2ª etapa  |  -.1056523   .0917057    -1.15   0.249    -.2855553   
>  .0742508
                 F.P.  |  -.0983112   .0912604    -1.08   0.282    -.2773407   
>  .0807184
           Superiores  |   -.096386   .0915634    -1.05   0.293    -.2760099   
>  .0832378
                       |
                 _cons |   .2109795   .1038991     2.03   0.042      .007156   
>   .414803
-------------------------------------------------------------------------------
---------

. est store pp_fe_controls

. regsave cabine_use_pp_dummy using 01_data/survey_data_2.dta, ci level(95) app
> end addlabel ///
> (Removed, Mun Size, Model, uncomfortable, FE, Without region fixed effects)
(variable Removed was str8, now str19 to accommodate using data's values)
file 01_data/survey_data_2.dta saved

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured9_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * A fake model to start the dataset
. regr cabine_use CCAA

      Source |       SS           df       MS      Number of obs   =     1,848
-------------+----------------------------------   F(1, 1846)      =      4.17
       Model |  1.02665746         1  1.02665746   Prob > F        =    0.0414
    Residual |  455.007433     1,846    .2464829   R-squared       =    0.0023
-------------+----------------------------------   Adj R-squared   =    0.0017
       Total |  456.034091     1,847  .246905301   Root MSE        =    .49647

------------------------------------------------------------------------------
  cabine_use | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        CCAA |  -.0046489   .0022779    -2.04   0.041    -.0091163   -.0001814
       _cons |   .4829034   .0226314    21.34   0.000     .4385175    .5272892
------------------------------------------------------------------------------

. regsave CCAA using 01_data/survey_ccaa_jk.dta, ci level(95) replace addlabel 
> ///
> (Removed, fake, Model, fake, Controls, fake)
file 01_data/survey_ccaa_jk.dta saved

. 
. * Actual analyses
. forvalues x = 1/19{
  2.         regr cabine_use pp_dummy female i.income age age_sq i.education i.
> TAMUNI i.CCAA if CCAA != `x', r
  3.         regsave pp_dummy using 01_data/survey_ccaa_jk.dta, ci level(95) ap
> pend addlabel ///
> (Removed, `x', Model, cabine_use, Controls, With controls)
  4. 
.         regr cabine_use pp_dummy if CCAA != `x', r
  5.         regsave pp_dummy using 01_data/survey_ccaa_jk.dta, ci level(95) ap
> pend addlabel ///
> (Removed, `x', Model, cabine_use, Controls, Without controls)
  6. }

Linear regression                               Number of obs     =      1,125
                                                F(42, 1082)       =      19.91
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2825
                                                Root MSE          =     .43038

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0681994   .0378275     1.80   0.072    -.0
> 060242                                                                       
>           .1424229
                         female |  -.0204183   .0279886    -0.73   0.466    -.0
> 753363                                                                       
>           .0344997
                                |
                         income |
         Menos o igual a 300 €  |   .0260729   .0997699     0.26   0.794    -.1
> 696914                                                                       
>           .2218373
                De 301 a 600 €  |  -.0057851   .0626921    -0.09   0.926     -.
> 128797                                                                       
>           .1172268
                De 601 a 900 €  |  -.0370335    .048063    -0.77   0.441    -.1
> 313407                                                                       
>           .0572738
              De 901 a 1.200 €  |  -.0207254   .0451154    -0.46   0.646    -.1
> 092491                                                                       
>           .0677983
            De 1.201 a 1.800 €  |    -.01268   .0477897    -0.27   0.791    -.1
> 064509                                                                       
>           .0810909
            De 1.801 a 2.400 €  |   .0009288    .056522     0.02   0.987    -.1
> 099764                                                                       
>            .111834
            De 2.401 a 3.000 €  |  -.0183867   .0776132    -0.24   0.813    -.1
> 706762                                                                       
>           .1339027
            De 3.001 a 4.500 €  |   .1362715   .1233353     1.10   0.269     -.
> 105732                                                                       
>            .378275
            De 4.501 a 6.000 €  |  -.4146879   .1802459    -2.30   0.022     -.
> 768359                                                                       
>          -.0610167
                Más de 6.000 €  |   .2309938   .1602285     1.44   0.150       
> -.0834                                                                       
>           .5453877
                                |
                            age |   .0022859   .0048683     0.47   0.639    -.0
> 072664                                                                       
>           .0118382
                         age_sq |  -.0000482   .0000505    -0.95   0.340    -.0
> 001474                                                                       
>           .0000509
                                |
                      education |
                      Primaria  |    .005705   .1186763     0.05   0.962    -.2
> 271567                                                                       
>           .2385667
           Secundaria 1ª etapa  |  -.0769112   .1200075    -0.64   0.522     -.
> 312385                                                                       
>           .1585627
           Secundaria 2ª etapa  |  -.1337332   .1212899    -1.10   0.270    -.3
> 717232                                                                       
>           .1042568
                          F.P.  |  -.0767356   .1203559    -0.64   0.524    -.3
> 128931                                                                       
>           .1594218
                    Superiores  |  -.0755217   .1213447    -0.62   0.534    -.3
> 136192                                                                       
>           .1625759
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0403455   .0614789     0.66   0.512    -.0
> 802857                                                                       
>           .1609768
    10.001 a 50.000 habitantes  |  -.1303661   .0601027    -2.17   0.030    -.2
> 482971                                                                       
>          -.0124351
   50.001 a 100.000 habitantes  |  -.2242952   .0679231    -3.30   0.001    -.3
> 575711                                                                       
>          -.0910193
  100.001 a 400.000 habitantes  |  -.2218732   .0618516    -3.59   0.000     -.
> 343236                                                                       
>          -.1005105
400.001 a 1.000.000 habitantes  |  -.3628071    .075172    -4.83   0.000    -.5
> 103065                                                                       
>          -.2153077
   Más de 1.000.000 habitantes  |  -.2437224   .0646848    -3.77   0.000    -.3
> 706443                                                                       
>          -.1168006
                                |
                           CCAA |
      Asturias (Principado de)  |   -.184351   .0931543    -1.98   0.048    -.3
> 671346                                                                       
>          -.0015675
               Balears (Illes)  |  -.1668563   .0901235    -1.85   0.064    -.3
> 436929                                                                       
>           .0099804
                      Canarias  |    .401202   .0790157     5.08   0.000     .2
> 461606                                                                       
>           .5562434
                     Cantabria  |  -.0339674   .0873198    -0.39   0.697    -.2
> 053028                                                                       
>            .137368
            Castilla-La Mancha  |   .0483412   .0918212     0.53   0.599    -.1
> 318266                                                                       
>           .2285089
               Castilla y León  |   .0803127   .0902978     0.89   0.374     -.
> 096866                                                                       
>           .2574914
                      Cataluña  |  -.4096065   .0749891    -5.46   0.000    -.5
> 567471                                                                       
>           -.262466
          Comunitat Valenciana  |  -.0515426   .0749791    -0.69   0.492    -.1
> 986635                                                                       
>           .0955783
                   Extremadura  |    .182382   .0814953     2.24   0.025     .0
> 224753                                                                       
>           .3422888
                       Galicia  |   .0002142   .0915765     0.00   0.998    -.1
> 794736                                                                       
>           .1799019
         Madrid (Comunidad de)  |  -.3565488   .0754137    -4.73   0.000    -.5
> 045224                                                                       
>          -.2085752
            Murcia (Región de)  |   .1629894   .0842067     1.94   0.053    -.0
> 022375                                                                       
>           .3282162
  Navarra (Comunidad Foral de)  |  -.1820279   .1065662    -1.71   0.088    -.3
> 911278                                                                       
>           .0270719
                    País Vasco  |  -.0771664   .1080923    -0.71   0.475    -.2
> 892606                                                                       
>           .1349279
                    Rioja (La)  |  -.0360282   .1208085    -0.30   0.766    -.2
> 730737                                                                       
>           .2010173
    Ceuta (Ciudad Autónoma de)  |   .3403669   .1096625     3.10   0.002     .1
> 251918                                                                       
>           .5555421
  Melilla (Ciudad Autónoma de)  |   .2103251   .1341861     1.57   0.117    -.0
> 529693                                                                       
>           .4736195
                                |
                          _cons |   .7934358   .1686178     4.71   0.000     .4
> 625809                                                                       
>           1.124291
-------------------------------------------------------------------------------
------------------
(note: variable Removed was str4 in the using data, but will be byte now)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,554
                                                F(1, 1552)        =       7.64
                                                Prob > F          =     0.0058
                                                R-squared         =     0.0050
                                                Root MSE          =     .49308

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1030201   .0372595     2.76   0.006     .0299359    .1761044
       _cons |   .4090572   .0134048    30.52   0.000     .3827637    .4353506
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,298
                                                F(42, 1255)       =      19.79
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2481
                                                Root MSE          =     .44042

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0899208   .0352731     2.55   0.011     .0
> 207199                                                                       
>           .1591216
                         female |  -.0185586   .0265585    -0.70   0.485    -.0
> 706626                                                                       
>           .0335454
                                |
                         income |
         Menos o igual a 300 €  |  -.0008547   .0956785    -0.01   0.993    -.1
> 885621                                                                       
>           .1868527
                De 301 a 600 €  |  -.0036721   .0568865    -0.06   0.949    -.1
> 152752                                                                       
>           .1079311
                De 601 a 900 €  |  -.0321461   .0454127    -0.71   0.479    -.1
> 212392                                                                       
>            .056947
              De 901 a 1.200 €  |  -.0483904   .0428665    -1.13   0.259    -.1
> 324883                                                                       
>           .0357074
            De 1.201 a 1.800 €  |  -.0332474   .0451754    -0.74   0.462     -.
> 121875                                                                       
>           .0553801
            De 1.801 a 2.400 €  |   .0018454   .0545491     0.03   0.973    -.1
> 051721                                                                       
>           .1088629
            De 2.401 a 3.000 €  |  -.0401503   .0731721    -0.55   0.583    -.1
> 837035                                                                       
>           .1034028
            De 3.001 a 4.500 €  |   .1537266   .1160326     1.32   0.185    -.0
> 739127                                                                       
>           .3813659
            De 4.501 a 6.000 €  |  -.4363391   .1792098    -2.43   0.015     -.
> 787923                                                                       
>          -.0847553
                Más de 6.000 €  |   .0222427   .2081411     0.11   0.915    -.3
> 861001                                                                       
>           .4305855
                                |
                            age |  -.0002796   .0046383    -0.06   0.952    -.0
> 093794                                                                       
>           .0088201
                         age_sq |  -.0000204   .0000484    -0.42   0.673    -.0
> 001155                                                                       
>           .0000746
                                |
                      education |
                      Primaria  |  -.0683189   .1057032    -0.65   0.518    -.2
> 756933                                                                       
>           .1390556
           Secundaria 1ª etapa  |  -.1400757   .1064347    -1.32   0.188    -.3
> 488852                                                                       
>           .0687338
           Secundaria 2ª etapa  |   -.174696   .1082385    -1.61   0.107    -.3
> 870444                                                                       
>           .0376524
                          F.P.  |  -.0930827   .1074272    -0.87   0.386    -.3
> 038394                                                                       
>           .1176739
                    Superiores  |    -.10549   .1091355    -0.97   0.334    -.3
> 195981                                                                       
>           .1086182
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0100112   .0636493     0.16   0.875    -.1
> 148595                                                                       
>           .1348818
    10.001 a 50.000 habitantes  |  -.1153435   .0620861    -1.86   0.063    -.2
> 371475                                                                       
>           .0064605
   50.001 a 100.000 habitantes  |  -.1750179   .0682134    -2.57   0.010    -.3
> 088427                                                                       
>          -.0411931
  100.001 a 400.000 habitantes  |  -.2090946   .0631818    -3.31   0.001    -.3
> 330482                                                                       
>          -.0851411
400.001 a 1.000.000 habitantes  |  -.3368565   .0769021    -4.38   0.000    -.4
> 877274                                                                       
>          -.1859856
   Más de 1.000.000 habitantes  |  -.2315317   .0668329    -3.46   0.001    -.3
> 626482                                                                       
>          -.1004153
                                |
                           CCAA |
      Asturias (Principado de)  |  -.2225233   .0725262    -3.07   0.002    -.3
> 648094                                                                       
>          -.0802373
               Balears (Illes)  |  -.1994603   .0774532    -2.58   0.010    -.3
> 514124                                                                       
>          -.0475082
                      Canarias  |   .3688893   .0541775     6.81   0.000     .2
> 626009                                                                       
>           .4751778
                     Cantabria  |  -.0538827   .0692277    -0.78   0.437    -.1
> 896975                                                                       
>            .081932
            Castilla-La Mancha  |   .0102006   .0713097     0.14   0.886    -.1
> 296987                                                                       
>           .1500999
               Castilla y León  |   .0539193   .0717507     0.75   0.453    -.0
> 868452                                                                       
>           .1946837
                      Cataluña  |  -.4363292    .048545    -8.99   0.000    -.5
> 315676                                                                       
>          -.3410908
          Comunitat Valenciana  |  -.0822039   .0545818    -1.51   0.132    -.1
> 892855                                                                       
>           .0248777
                   Extremadura  |   .1590074   .0617586     2.57   0.010     .0
> 378458                                                                       
>            .280169
                       Galicia  |  -.0267311   .0722272    -0.37   0.711    -.1
> 684305                                                                       
>           .1149683
         Madrid (Comunidad de)  |  -.3910271   .0475256    -8.23   0.000    -.4
> 842655                                                                       
>          -.2977886
            Murcia (Región de)  |    .125054   .0662188     1.89   0.059    -.0
> 048578                                                                       
>           .2549658
  Navarra (Comunidad Foral de)  |  -.2009134   .0912364    -2.20   0.028    -.3
> 799062                                                                       
>          -.0219207
                    País Vasco  |   -.115774   .0893771    -1.30   0.195     -.
> 291119                                                                       
>           .0595709
                    Rioja (La)  |   -.065835   .1063899    -0.62   0.536    -.2
> 745567                                                                       
>           .1428866
    Ceuta (Ciudad Autónoma de)  |   .2706457   .0874137     3.10   0.002     .0
> 991527                                                                       
>           .4421388
  Melilla (Ciudad Autónoma de)  |   .1421763   .1153655     1.23   0.218    -.0
> 841542                                                                       
>           .3685067
                                |
                          _cons |   .9114576   .1481836     6.15   0.000     .6
> 207427                                                                       
>           1.202173
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,772
                                                F(1, 1770)        =      10.29
                                                Prob > F          =     0.0014
                                                R-squared         =     0.0058
                                                Root MSE          =      .4955

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1087406   .0339008     3.21   0.001     .0422508    .1752304
       _cons |   .4269737   .0126944    33.63   0.000     .4020761    .4518712
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,306
                                                F(42, 1263)       =      20.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2517
                                                Root MSE          =     .43958

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |    .089515   .0349674     2.56   0.011     .0
> 209145                                                                       
>           .1581155
                         female |  -.0130638   .0263359    -0.50   0.620    -.0
> 647307                                                                       
>           .0386031
                                |
                         income |
         Menos o igual a 300 €  |    .013978   .0928871     0.15   0.880     -.
> 168252                                                                       
>            .196208
                De 301 a 600 €  |  -.0037246   .0570313    -0.07   0.948     -.
> 115611                                                                       
>           .1081619
                De 601 a 900 €  |  -.0423668   .0455107    -0.93   0.352    -.1
> 316517                                                                       
>           .0469181
              De 901 a 1.200 €  |  -.0447899   .0429647    -1.04   0.297    -.1
> 290799                                                                       
>           .0395001
            De 1.201 a 1.800 €  |   -.014749   .0457609    -0.32   0.747    -.1
> 045248                                                                       
>           .0750268
            De 1.801 a 2.400 €  |   .0101003   .0541808     0.19   0.852    -.0
> 961939                                                                       
>           .1163945
            De 2.401 a 3.000 €  |  -.0176968   .0747446    -0.24   0.813     -.
> 164334                                                                       
>           .1289404
            De 3.001 a 4.500 €  |   .1533733   .1097412     1.40   0.162    -.0
> 619218                                                                       
>           .3686685
            De 4.501 a 6.000 €  |  -.4164334   .1757302    -2.37   0.018    -.7
> 611887                                                                       
>          -.0716781
                Más de 6.000 €  |   .0171034   .2082378     0.08   0.935    -.3
> 914267                                                                       
>           .4256335
                                |
                            age |  -.0006797    .004595    -0.15   0.882    -.0
> 096943                                                                       
>           .0083349
                         age_sq |  -.0000113   .0000478    -0.24   0.813    -.0
> 001051                                                                       
>           .0000825
                                |
                      education |
                      Primaria  |  -.0375205   .1099308    -0.34   0.733    -.2
> 531875                                                                       
>           .1781465
           Secundaria 1ª etapa  |  -.1207989    .111067    -1.09   0.277    -.3
> 386949                                                                       
>           .0970972
           Secundaria 2ª etapa  |  -.1520536   .1127701    -1.35   0.178     -.
> 373291                                                                       
>           .0691838
                          F.P.  |  -.0726603   .1118635    -0.65   0.516     -.
> 292119                                                                       
>           .1467985
                    Superiores  |  -.0933711    .113341    -0.82   0.410    -.3
> 157285                                                                       
>           .1289863
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0007185   .0597275     0.01   0.990    -.1
> 164575                                                                       
>           .1178946
    10.001 a 50.000 habitantes  |  -.1214222   .0581373    -2.09   0.037    -.2
> 354785                                                                       
>          -.0073659
   50.001 a 100.000 habitantes  |  -.1522136   .0650969    -2.34   0.020    -.2
> 799237                                                                       
>          -.0245036
  100.001 a 400.000 habitantes  |     -.2299   .0601438    -3.82   0.000    -.3
> 478928                                                                       
>          -.1119073
400.001 a 1.000.000 habitantes  |  -.3805047   .0680117    -5.59   0.000     -.
> 513933                                                                       
>          -.2470763
   Más de 1.000.000 habitantes  |  -.2401974   .0637643    -3.77   0.000     -.
> 365293                                                                       
>          -.1151018
                                |
                           CCAA |
                        Aragón  |  -.0252167   .0687566    -0.37   0.714    -.1
> 601064                                                                       
>            .109673
               Balears (Illes)  |  -.1878195    .077884    -2.41   0.016    -.3
> 406159                                                                       
>          -.0350232
                      Canarias  |   .3682351   .0539317     6.83   0.000     .2
> 624296                                                                       
>           .4740407
                     Cantabria  |  -.0631666   .0681138    -0.93   0.354    -.1
> 967952                                                                       
>           .0704621
            Castilla-La Mancha  |  -.0016229   .0709431    -0.02   0.982    -.1
> 408021                                                                       
>           .1375564
               Castilla y León  |    .043362   .0713513     0.61   0.543     -.
> 096618                                                                       
>           .1833421
                      Cataluña  |  -.4441287   .0483219    -9.19   0.000    -.5
> 389288                                                                       
>          -.3493286
          Comunitat Valenciana  |  -.0856252   .0545202    -1.57   0.117    -.1
> 925852                                                                       
>           .0213348
                   Extremadura  |   .1518449    .061565     2.47   0.014     .0
> 310641                                                                       
>           .2726258
                       Galicia  |  -.0337396   .0726243    -0.46   0.642    -.1
> 762171                                                                       
>           .1087379
         Madrid (Comunidad de)  |  -.4001278   .0473273    -8.45   0.000    -.4
> 929766                                                                       
>           -.307279
            Murcia (Región de)  |   .1321196   .0661756     2.00   0.046     .0
> 022933                                                                       
>           .2619459
  Navarra (Comunidad Foral de)  |   -.205092   .0904858    -2.27   0.024    -.3
> 826109                                                                       
>          -.0275731
                    País Vasco  |  -.1174883   .0884608    -1.33   0.184    -.2
> 910345                                                                       
>           .0560579
                    Rioja (La)  |  -.0647216   .1052851    -0.61   0.539    -.2
> 712746                                                                       
>           .1418314
    Ceuta (Ciudad Autónoma de)  |   .2316901   .0882533     2.63   0.009     .0
> 585509                                                                       
>           .4048292
  Melilla (Ciudad Autónoma de)  |   .1106579   .1161426     0.95   0.341    -.1
> 171959                                                                       
>           .3385116
                                |
                          _cons |   .8955053   .1495522     5.99   0.000     .6
> 021072                                                                       
>           1.188903
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,785
                                                F(1, 1783)        =      10.57
                                                Prob > F          =     0.0012
                                                R-squared         =     0.0059
                                                Root MSE          =     .49599

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1102812   .0339154     3.25   0.001     .0437631    .1767992
       _cons |   .4315515    .012653    34.11   0.000     .4067353    .4563677
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,307
                                                F(42, 1264)       =      20.66
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2562
                                                Root MSE          =     .43828

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1102904   .0352758     3.13   0.002     .0
> 410848                                                                       
>            .179496
                         female |  -.0184939   .0265277    -0.70   0.486    -.0
> 705371                                                                       
>           .0335493
                                |
                         income |
         Menos o igual a 300 €  |     .00028   .0929612     0.00   0.998    -.1
> 820952                                                                       
>           .1826553
                De 301 a 600 €  |  -.0028698   .0566697    -0.05   0.960    -.1
> 140469                                                                       
>           .1083073
                De 601 a 900 €  |    -.03784   .0451536    -0.84   0.402    -.1
> 264242                                                                       
>           .0507442
              De 901 a 1.200 €  |  -.0427397   .0428236    -1.00   0.318    -.1
> 267528                                                                       
>           .0412734
            De 1.201 a 1.800 €  |  -.0239598   .0453884    -0.53   0.598    -.1
> 130046                                                                       
>            .065085
            De 1.801 a 2.400 €  |  -.0168765   .0538385    -0.31   0.754    -.1
> 224992                                                                       
>           .0887462
            De 2.401 a 3.000 €  |  -.0663176   .0730996    -0.91   0.364    -.2
> 097274                                                                       
>           .0770923
            De 3.001 a 4.500 €  |   .1636543   .1123539     1.46   0.145    -.0
> 567663                                                                       
>            .384075
            De 4.501 a 6.000 €  |  -.4359368   .1755896    -2.48   0.013     -.
> 780416                                                                       
>          -.0914576
                Más de 6.000 €  |   .0214451   .2151504     0.10   0.921    -.4
> 006462                                                                       
>           .4435363
                                |
                            age |   .0005049   .0045246     0.11   0.911    -.0
> 083717                                                                       
>           .0093815
                         age_sq |  -.0000265   .0000469    -0.56   0.572    -.0
> 001185                                                                       
>           .0000655
                                |
                      education |
                      Primaria  |  -.0761921   .1076381    -0.71   0.479     -.
> 287361                                                                       
>           .1349768
           Secundaria 1ª etapa  |  -.1583891   .1084581    -1.46   0.144    -.3
> 711667                                                                       
>           .0543886
           Secundaria 2ª etapa  |  -.1789279   .1102221    -1.62   0.105    -.3
> 951664                                                                       
>           .0373106
                          F.P.  |  -.0999774   .1093288    -0.91   0.361    -.3
> 144632                                                                       
>           .1145085
                    Superiores  |  -.1182031   .1107963    -1.07   0.286     -.
> 335568                                                                       
>           .0991618
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0112915   .0600468     0.19   0.851    -.1
> 065108                                                                       
>           .1290939
    10.001 a 50.000 habitantes  |  -.1014175   .0586793    -1.73   0.084    -.2
> 165371                                                                       
>           .0137021
   50.001 a 100.000 habitantes  |  -.1670208   .0647326    -2.58   0.010     -.
> 294016                                                                       
>          -.0400256
  100.001 a 400.000 habitantes  |  -.2078024   .0601984    -3.45   0.001    -.3
> 259022                                                                       
>          -.0897027
400.001 a 1.000.000 habitantes  |  -.4162216   .0699553    -5.95   0.000     -.
> 553463                                                                       
>          -.2789802
   Más de 1.000.000 habitantes  |  -.2250115   .0640548    -3.51   0.000    -.3
> 506769                                                                       
>           -.099346
                                |
                           CCAA |
                        Aragón  |  -.0048274   .0686869    -0.07   0.944    -.1
> 395802                                                                       
>           .1299255
      Asturias (Principado de)  |  -.2338498    .072727    -3.22   0.001    -.3
> 765287                                                                       
>          -.0911709
                      Canarias  |   .3564332   .0542797     6.57   0.000      .
> 249945                                                                       
>           .4629215
                     Cantabria  |  -.0689073   .0687105    -1.00   0.316    -.2
> 037065                                                                       
>           .0658918
            Castilla-La Mancha  |  -.0059104   .0710269    -0.08   0.934     -.
> 145254                                                                       
>           .1334332
               Castilla y León  |   .0399037   .0710429     0.56   0.574    -.0
> 994713                                                                       
>           .1792787
                      Cataluña  |  -.4476616   .0483511    -9.26   0.000    -.5
> 425188                                                                       
>          -.3528044
          Comunitat Valenciana  |  -.0809573   .0544887    -1.49   0.138    -.1
> 878556                                                                       
>            .025941
                   Extremadura  |   .1453583   .0611159     2.38   0.018     .0
> 254586                                                                       
>           .2652581
                       Galicia  |  -.0429326   .0724308    -0.59   0.553    -.1
> 850304                                                                       
>           .0991652
         Madrid (Comunidad de)  |  -.4062732   .0473084    -8.59   0.000    -.4
> 990849                                                                       
>          -.3134615
            Murcia (Región de)  |   .1367935   .0666995     2.05   0.040     .0
> 059396                                                                       
>           .2676473
  Navarra (Comunidad Foral de)  |  -.2115199   .0913389    -2.32   0.021    -.3
> 907124                                                                       
>          -.0323273
                    País Vasco  |   -.124797   .0885786    -1.41   0.159    -.2
> 985743                                                                       
>           .0489802
                    Rioja (La)  |  -.0811231   .1059915    -0.77   0.444    -.2
> 890618                                                                       
>           .1268156
    Ceuta (Ciudad Autónoma de)  |   .2516435   .0872801     2.88   0.004     .0
> 804137                                                                       
>           .4228733
  Melilla (Ciudad Autónoma de)  |    .124319   .1154696     1.08   0.282    -.1
> 022142                                                                       
>           .3508521
                                |
                          _cons |   .9058576   .1481662     6.11   0.000     .6
> 151789                                                                       
>           1.196536
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,768
                                                F(1, 1766)        =      13.15
                                                Prob > F          =     0.0003
                                                R-squared         =     0.0075
                                                Root MSE          =     .49528

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1245551   .0343465     3.63   0.000      .057191    .1919191
       _cons |   .4268852   .0126732    33.68   0.000     .4020291    .4517414
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,316
                                                F(42, 1273)       =      15.98
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2316
                                                Root MSE          =     .44445

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |    .096127   .0351931     2.73   0.006     .0
> 270842                                                                       
>           .1651699
                         female |  -.0188216   .0265284    -0.71   0.478    -.0
> 708657                                                                       
>           .0332226
                                |
                         income |
         Menos o igual a 300 €  |  -.0088929   .0955223    -0.09   0.926    -.1
> 962913                                                                       
>           .1785055
                De 301 a 600 €  |    .007711   .0575674     0.13   0.893    -.1
> 052264                                                                       
>           .1206485
                De 601 a 900 €  |  -.0369728     .04593    -0.80   0.421    -.1
> 270796                                                                       
>           .0531341
              De 901 a 1.200 €  |  -.0473069   .0432038    -1.09   0.274    -.1
> 320653                                                                       
>           .0374516
            De 1.201 a 1.800 €  |  -.0222606   .0452461    -0.49   0.623    -.1
> 110257                                                                       
>           .0665044
            De 1.801 a 2.400 €  |   .0041691   .0546883     0.08   0.939    -.1
> 031201                                                                       
>           .1114582
            De 2.401 a 3.000 €  |  -.0325692   .0733758    -0.44   0.657      -
> .17652                                                                       
>           .1113815
            De 3.001 a 4.500 €  |    .150809   .1098663     1.37   0.170    -.0
> 647299                                                                       
>            .366348
            De 4.501 a 6.000 €  |   -.423581   .1820014    -2.33   0.020    -.7
> 806367                                                                       
>          -.0665253
                Más de 6.000 €  |   .0231976   .2101223     0.11   0.912    -.3
> 890265                                                                       
>           .4354217
                                |
                            age |  -.0003752   .0045767    -0.08   0.935    -.0
> 093538                                                                       
>           .0086035
                         age_sq |  -.0000185   .0000476    -0.39   0.698    -.0
> 001118                                                                       
>           .0000748
                                |
                      education |
                      Primaria  |  -.0615677   .1055697    -0.58   0.560    -.2
> 686774                                                                       
>           .1455421
           Secundaria 1ª etapa  |  -.1406011    .106479    -1.32   0.187    -.3
> 494947                                                                       
>           .0682925
           Secundaria 2ª etapa  |  -.1649731   .1080988    -1.53   0.127    -.3
> 770445                                                                       
>           .0470983
                          F.P.  |  -.0820767   .1072537    -0.77   0.444    -.2
> 924901                                                                       
>           .1283367
                    Superiores  |  -.1058093   .1087964    -0.97   0.331    -.3
> 192493                                                                       
>           .1076306
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0042744   .0598599     0.07   0.943    -.1
> 131604                                                                       
>           .1217092
    10.001 a 50.000 habitantes  |  -.1312383    .058479    -2.24   0.025    -.2
> 459642                                                                       
>          -.0165124
   50.001 a 100.000 habitantes  |  -.1812328   .0650499    -2.79   0.005    -.3
> 088497                                                                       
>           -.053616
  100.001 a 400.000 habitantes  |  -.2189945   .0603639    -3.63   0.000    -.3
> 374181                                                                       
>          -.1005708
400.001 a 1.000.000 habitantes  |   -.385457   .0680075    -5.67   0.000     -.
> 518876                                                                       
>          -.2520379
   Más de 1.000.000 habitantes  |  -.2414545   .0638761    -3.78   0.000    -.3
> 667686                                                                       
>          -.1161404
                                |
                           CCAA |
                        Aragón  |  -.0224431   .0689707    -0.33   0.745    -.1
> 577518                                                                       
>           .1128656
      Asturias (Principado de)  |  -.2293799   .0725295    -3.16   0.002    -.3
> 716703                                                                       
>          -.0870895
               Balears (Illes)  |  -.1846581   .0779232    -2.37   0.018      -
> .33753                                                                       
>          -.0317862
                     Cantabria  |  -.0650453   .0686481    -0.95   0.344    -.1
> 997211                                                                       
>           .0696305
            Castilla-La Mancha  |    .002541   .0710729     0.04   0.971    -.1
> 368919                                                                       
>            .141974
               Castilla y León  |   .0421256   .0712725     0.59   0.555    -.0
> 976989                                                                       
>             .18195
                      Cataluña  |  -.4450022   .0482417    -9.22   0.000    -.5
> 396443                                                                       
>          -.3503602
          Comunitat Valenciana  |   -.082414   .0545041    -1.51   0.131    -.1
> 893417                                                                       
>           .0245137
                   Extremadura  |    .150579   .0611322     2.46   0.014     .0
> 306481                                                                       
>           .2705098
                       Galicia  |  -.0334696   .0722402    -0.46   0.643    -.1
> 751925                                                                       
>           .1082534
         Madrid (Comunidad de)  |  -.3994331   .0472981    -8.45   0.000    -.4
> 922239                                                                       
>          -.3066423
            Murcia (Región de)  |   .1325155    .066444     1.99   0.046     .0
> 021637                                                                       
>           .2628673
  Navarra (Comunidad Foral de)  |  -.2087176   .0914803    -2.28   0.023    -.3
> 881863                                                                       
>          -.0292489
                    País Vasco  |  -.1228367   .0888647    -1.38   0.167    -.2
> 971741                                                                       
>           .0515007
                    Rioja (La)  |  -.0762709   .1059627    -0.72   0.472    -.2
> 841516                                                                       
>           .1316099
    Ceuta (Ciudad Autónoma de)  |   .2574217   .0876313     2.94   0.003      .
> 085504                                                                       
>           .4293394
  Melilla (Ciudad Autónoma de)  |   .1320683   .1152797     1.15   0.252    -.0
> 940908                                                                       
>           .3582274
                                |
                          _cons |   .9206123   .1469013     6.27   0.000     .6
> 324171                                                                       
>           1.208808
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,796
                                                F(1, 1794)        =      13.43
                                                Prob > F          =     0.0003
                                                R-squared         =     0.0076
                                                Root MSE          =     .49337

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1236302   .0337292     3.67   0.000     .0574776    .1897829
       _cons |   .4118029   .0125402    32.84   0.000     .3872078    .4363979
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,288
                                                F(42, 1245)       =      20.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2565
                                                Root MSE          =     .43778

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1087809   .0357018     3.05   0.002     .0
> 387386                                                                       
>           .1788232
                         female |  -.0152304   .0263703    -0.58   0.564    -.0
> 669656                                                                       
>           .0365048
                                |
                         income |
         Menos o igual a 300 €  |  -.0056149   .0894797    -0.06   0.950    -.1
> 811626                                                                       
>           .1699328
                De 301 a 600 €  |   .0073387   .0573505     0.13   0.898    -.1
> 051757                                                                       
>           .1198531
                De 601 a 900 €  |  -.0216361   .0456026    -0.47   0.635    -.1
> 111024                                                                       
>           .0678303
              De 901 a 1.200 €  |  -.0526414   .0433738    -1.21   0.225    -.1
> 377352                                                                       
>           .0324524
            De 1.201 a 1.800 €  |  -.0318182   .0459678    -0.69   0.489     -.
> 122001                                                                       
>           .0583647
            De 1.801 a 2.400 €  |    .008242   .0542313     0.15   0.879    -.0
> 981528                                                                       
>           .1146367
            De 2.401 a 3.000 €  |  -.0210769   .0739599    -0.28   0.776    -.1
> 661767                                                                       
>           .1240228
            De 3.001 a 4.500 €  |   .2120841   .1095135     1.94   0.053    -.0
> 027673                                                                       
>           .4269354
            De 4.501 a 6.000 €  |  -.4377329   .1853431    -2.36   0.018    -.8
> 013522                                                                       
>          -.0741137
                Más de 6.000 €  |  -.0200657   .2483122    -0.08   0.936    -.5
> 072223                                                                       
>           .4670909
                                |
                            age |  -.0005951   .0046422    -0.13   0.898    -.0
> 097025                                                                       
>           .0085123
                         age_sq |   -.000019   .0000483    -0.39   0.694    -.0
> 001137                                                                       
>           .0000758
                                |
                      education |
                      Primaria  |  -.0714937   .1060906    -0.67   0.501    -.2
> 796297                                                                       
>           .1366424
           Secundaria 1ª etapa  |   -.143607   .1071259    -1.34   0.180    -.3
> 537742                                                                       
>           .0665602
           Secundaria 2ª etapa  |  -.1605353   .1087482    -1.48   0.140    -.3
> 738852                                                                       
>           .0528146
                          F.P.  |   -.095902    .108033    -0.89   0.375     -.
> 307849                                                                       
>           .1160449
                    Superiores  |  -.1003165   .1093777    -0.92   0.359    -.3
> 149015                                                                       
>           .1142685
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0046516   .0644335     0.07   0.942    -.1
> 217586                                                                       
>           .1310619
    10.001 a 50.000 habitantes  |  -.1223962   .0621294    -1.97   0.049     -.
> 244286                                                                       
>          -.0005063
   50.001 a 100.000 habitantes  |  -.1775567     .06814    -2.61   0.009    -.3
> 112385                                                                       
>          -.0438748
  100.001 a 400.000 habitantes  |  -.1905422   .0636315    -2.99   0.003    -.3
> 153789                                                                       
>          -.0657054
400.001 a 1.000.000 habitantes  |  -.3795888   .0706171    -5.38   0.000    -.5
> 181305                                                                       
>          -.2410472
   Más de 1.000.000 habitantes  |  -.2283036   .0669319    -3.41   0.001    -.3
> 596154                                                                       
>          -.0969917
                                |
                           CCAA |
                        Aragón  |  -.0149671   .0695388    -0.22   0.830    -.1
> 513933                                                                       
>           .1214592
      Asturias (Principado de)  |  -.2352058    .071877    -3.27   0.001    -.3
> 762193                                                                       
>          -.0941923
               Balears (Illes)  |  -.1817229   .0779459    -2.33   0.020    -.3
> 346428                                                                       
>           -.028803
                      Canarias  |   .3600367   .0541869     6.64   0.000      .
> 253729                                                                       
>           .4663444
            Castilla-La Mancha  |   .0044411    .071523     0.06   0.950    -.1
> 358779                                                                       
>           .1447601
               Castilla y León  |    .044265   .0716518     0.62   0.537    -.0
> 963066                                                                       
>           .1848367
                      Cataluña  |  -.4427364   .0480549    -9.21   0.000     -.
> 537014                                                                       
>          -.3484589
          Comunitat Valenciana  |  -.0781453     .05438    -1.44   0.151    -.1
> 848319                                                                       
>           .0285414
                   Extremadura  |   .1517384   .0612357     2.48   0.013     .0
> 316019                                                                       
>            .271875
                       Galicia  |  -.0304251   .0719203    -0.42   0.672    -.1
> 715236                                                                       
>           .1106734
         Madrid (Comunidad de)  |  -.4033692   .0471753    -8.55   0.000     -.
> 495921                                                                       
>          -.3108174
            Murcia (Región de)  |   .1325096   .0667778     1.98   0.047     .0
> 015002                                                                       
>           .2635191
  Navarra (Comunidad Foral de)  |  -.2059477   .0911996    -2.26   0.024    -.3
> 848696                                                                       
>          -.0270258
                    País Vasco  |   -.123542    .089671    -1.38   0.169    -.2
> 994649                                                                       
>           .0523809
                    Rioja (La)  |  -.0898781   .1073736    -0.84   0.403    -.3
> 005312                                                                       
>           .1207751
    Ceuta (Ciudad Autónoma de)  |   .2682111   .0869189     3.09   0.002     .0
> 976874                                                                       
>           .4387348
  Melilla (Ciudad Autónoma de)  |   .1374779   .1145647     1.20   0.230    -.0
> 872832                                                                       
>            .362239
                                |
                          _cons |   .9184542   .1499588     6.12   0.000     .6
> 242543                                                                       
>           1.212654
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,768
                                                F(1, 1766)        =      12.26
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0070
                                                Root MSE          =     .49459

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1206146   .0344536     3.50   0.000     .0530404    .1881887
       _cons |   .4207077   .0126447    33.27   0.000     .3959076    .4455078
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,300
                                                F(42, 1257)       =      19.92
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2523
                                                Root MSE          =     .43892

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |    .086337   .0361327     2.39   0.017     .0
> 154499                                                                       
>           .1572241
                         female |  -.0065364   .0264654    -0.25   0.805    -.0
> 584576                                                                       
>           .0453848
                                |
                         income |
         Menos o igual a 300 €  |  -.0559539   .0979324    -0.57   0.568     -.
> 248083                                                                       
>           .1361751
                De 301 a 600 €  |   .0070163   .0567412     0.12   0.902    -.1
> 043017                                                                       
>           .1183343
                De 601 a 900 €  |  -.0337045   .0458309    -0.74   0.462     -.
> 123618                                                                       
>           .0562089
              De 901 a 1.200 €  |  -.0571809   .0434435    -1.32   0.188    -.1
> 424107                                                                       
>           .0280489
            De 1.201 a 1.800 €  |  -.0047699   .0455248    -0.10   0.917    -.0
> 940829                                                                       
>           .0845431
            De 1.801 a 2.400 €  |   .0059667   .0543489     0.11   0.913    -.1
> 006578                                                                       
>           .1125912
            De 2.401 a 3.000 €  |  -.0208079   .0741942    -0.28   0.779     -.
> 166366                                                                       
>           .1247502
            De 3.001 a 4.500 €  |   .1905228   .1087954     1.75   0.080    -.0
> 229177                                                                       
>           .4039633
            De 4.501 a 6.000 €  |  -.4296396   .1789613    -2.40   0.017    -.7
> 807354                                                                       
>          -.0785438
                Más de 6.000 €  |   .0413644   .2096905     0.20   0.844    -.3
> 700176                                                                       
>           .4527464
                                |
                            age |   -.001506   .0045967    -0.33   0.743    -.0
> 105241                                                                       
>           .0075121
                         age_sq |  -8.53e-06   .0000478    -0.18   0.858    -.0
> 001022                                                                       
>           .0000852
                                |
                      education |
                      Primaria  |  -.0222964   .1113318    -0.20   0.841    -.2
> 407131                                                                       
>           .1961203
           Secundaria 1ª etapa  |   -.095949    .111851    -0.86   0.391    -.3
> 153842                                                                       
>           .1234863
           Secundaria 2ª etapa  |  -.1306045   .1136127    -1.15   0.251     -.
> 353496                                                                       
>           .0922869
                          F.P.  |  -.0570871   .1127956    -0.51   0.613    -.2
> 783755                                                                       
>           .1642012
                    Superiores  |  -.0685124   .1141139    -0.60   0.548    -.2
> 923871                                                                       
>           .1553623
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0023828   .0612644    -0.04   0.969    -.1
> 225746                                                                       
>            .117809
    10.001 a 50.000 habitantes  |  -.1209978   .0593134    -2.04   0.042    -.2
> 373619                                                                       
>          -.0046336
   50.001 a 100.000 habitantes  |  -.1811198   .0663226    -2.73   0.006     -.
> 311235                                                                       
>          -.0510045
  100.001 a 400.000 habitantes  |  -.2088161   .0610019    -3.42   0.001    -.3
> 284929                                                                       
>          -.0891393
400.001 a 1.000.000 habitantes  |  -.3817765   .0685853    -5.57   0.000    -.5
> 163307                                                                       
>          -.2472222
   Más de 1.000.000 habitantes  |  -.2381649   .0645449    -3.69   0.000    -.3
> 647926                                                                       
>          -.1115372
                                |
                           CCAA |
                        Aragón  |  -.0230649   .0690818    -0.33   0.739    -.1
> 585933                                                                       
>           .1124636
      Asturias (Principado de)  |  -.2307522   .0726463    -3.18   0.002    -.3
> 732734                                                                       
>          -.0882309
               Balears (Illes)  |  -.1867376   .0778147    -2.40   0.017    -.3
> 393987                                                                       
>          -.0340765
                      Canarias  |   .3638443   .0542898     6.70   0.000     .2
> 573356                                                                       
>            .470353
                     Cantabria  |  -.0636386   .0689815    -0.92   0.356    -.1
> 989702                                                                       
>            .071693
               Castilla y León  |   .0397803   .0710867     0.56   0.576    -.0
> 996813                                                                       
>            .179242
                      Cataluña  |   -.448169   .0482929    -9.28   0.000    -.5
> 429126                                                                       
>          -.3534254
          Comunitat Valenciana  |  -.0838202   .0543444    -1.54   0.123     -.
> 190436                                                                       
>           .0227955
                   Extremadura  |   .1550175   .0608827     2.55   0.011     .0
> 355746                                                                       
>           .2744603
                       Galicia  |  -.0315529   .0720759    -0.44   0.662    -.1
> 729552                                                                       
>           .1098494
         Madrid (Comunidad de)  |  -.4016034   .0474156    -8.47   0.000    -.4
> 946258                                                                       
>           -.308581
            Murcia (Región de)  |    .130235   .0664575     1.96   0.050    -.0
> 001449                                                                       
>           .2606148
  Navarra (Comunidad Foral de)  |  -.2070413   .0906109    -2.28   0.022    -.3
> 848064                                                                       
>          -.0292761
                    País Vasco  |  -.1266287   .0888453    -1.43   0.154    -.3
> 009301                                                                       
>           .0476727
                    Rioja (La)  |  -.0810004   .1061264    -0.76   0.445    -.2
> 892048                                                                       
>            .127204
    Ceuta (Ciudad Autónoma de)  |   .2587371   .0882273     2.93   0.003     .0
> 856482                                                                       
>            .431826
  Melilla (Ciudad Autónoma de)  |   .1453301   .1161063     1.25   0.211    -.0
> 824534                                                                       
>           .3731136
                                |
                          _cons |   .9023225   .1536927     5.87   0.000       
>  .6008                                                                       
>           1.203845
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,784
                                                F(1, 1782)        =       8.85
                                                Prob > F          =     0.0030
                                                R-squared         =     0.0050
                                                Root MSE          =     .49493

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1026144   .0344971     2.97   0.003     .0349553    .1702735
       _cons |    .422179   .0125848    33.55   0.000     .3974965    .4468615
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,302
                                                F(42, 1259)       =      19.42
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2496
                                                Root MSE          =     .43963

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0930416   .0359255     2.59   0.010     .0
> 225612                                                                       
>           .1635221
                         female |  -.0161176   .0264939    -0.61   0.543    -.0
> 680947                                                                       
>           .0358595
                                |
                         income |
         Menos o igual a 300 €  |   .0061431    .090693     0.07   0.946     -.
> 171783                                                                       
>           .1840692
                De 301 a 600 €  |   .0095437   .0582036     0.16   0.870     -.
> 104643                                                                       
>           .1237303
                De 601 a 900 €  |  -.0125394   .0460153    -0.27   0.785    -.1
> 028145                                                                       
>           .0777357
              De 901 a 1.200 €  |  -.0327549   .0433466    -0.76   0.450    -.1
> 177946                                                                       
>           .0522847
            De 1.201 a 1.800 €  |  -.0148207   .0462312    -0.32   0.749    -.1
> 055194                                                                       
>           .0758781
            De 1.801 a 2.400 €  |   .0298144   .0539765     0.55   0.581    -.0
> 760795                                                                       
>           .1357083
            De 2.401 a 3.000 €  |  -.0033527   .0740726    -0.05   0.964     -.
> 148672                                                                       
>           .1419666
            De 3.001 a 4.500 €  |   .1589456   .1135689     1.40   0.162    -.0
> 638596                                                                       
>           .3817509
            De 4.501 a 6.000 €  |  -.4042488    .178366    -2.27   0.024    -.7
> 541761                                                                       
>          -.0543214
                Más de 6.000 €  |   .0410491   .2089189     0.20   0.844    -.3
> 688185                                                                       
>           .4509167
                                |
                            age |  -.0011548   .0047196    -0.24   0.807    -.0
> 104139                                                                       
>           .0081043
                         age_sq |  -.0000147   .0000491    -0.30   0.764    -.0
> 001111                                                                       
>           .0000816
                                |
                      education |
                      Primaria  |   -.068305   .1062523    -0.64   0.520    -.2
> 767561                                                                       
>            .140146
           Secundaria 1ª etapa  |  -.1463718   .1069526    -1.37   0.171    -.3
> 561968                                                                       
>           .0634532
           Secundaria 2ª etapa  |  -.1679002   .1085743    -1.55   0.122    -.3
> 809068                                                                       
>           .0451063
                          F.P.  |   -.094379   .1077936    -0.88   0.381    -.3
> 058538                                                                       
>           .1170958
                    Superiores  |  -.1209379   .1091752    -1.11   0.268    -.3
> 351233                                                                       
>           .0932474
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0084189    .063603     0.13   0.895    -.1
> 163607                                                                       
>           .1331984
    10.001 a 50.000 habitantes  |  -.1215638   .0614308    -1.98   0.048    -.2
> 420819                                                                       
>          -.0010458
   50.001 a 100.000 habitantes  |  -.1541286   .0679617    -2.27   0.024    -.2
> 874592                                                                       
>           -.020798
  100.001 a 400.000 habitantes  |  -.2105597   .0637563    -3.30   0.001    -.3
> 356399                                                                       
>          -.0854795
400.001 a 1.000.000 habitantes  |  -.3747366   .0704544    -5.32   0.000    -.5
> 129575                                                                       
>          -.2365156
   Más de 1.000.000 habitantes  |  -.2291318   .0669472    -3.42   0.001    -.3
> 604722                                                                       
>          -.0977914
                                |
                           CCAA |
                        Aragón  |  -.0214035   .0691424    -0.31   0.757    -.1
> 570505                                                                       
>           .1142436
      Asturias (Principado de)  |    -.23286    .072673    -3.20   0.001    -.3
> 754334                                                                       
>          -.0902865
               Balears (Illes)  |  -.1862831   .0775891    -2.40   0.016    -.3
> 385013                                                                       
>          -.0340649
                      Canarias  |   .3626891   .0540706     6.71   0.000     .2
> 566107                                                                       
>           .4687675
                     Cantabria  |  -.0606319   .0688453    -0.88   0.379     -.
> 195696                                                                       
>           .0744322
            Castilla-La Mancha  |   .0000494   .0707857     0.00   0.999    -.1
> 388215                                                                       
>           .1389204
                      Cataluña  |  -.4440308   .0482786    -9.20   0.000    -.5
> 387461                                                                       
>          -.3493155
          Comunitat Valenciana  |  -.0819228   .0543381    -1.51   0.132    -.1
> 885259                                                                       
>           .0246803
                   Extremadura  |   .1533376   .0617487     2.48   0.013     .0
> 321959                                                                       
>           .2744793
                       Galicia  |  -.0303858   .0724005    -0.42   0.675    -.1
> 724248                                                                       
>           .1116532
         Madrid (Comunidad de)  |  -.4008557   .0472943    -8.48   0.000    -.4
> 936401                                                                       
>          -.3080713
            Murcia (Región de)  |   .1326418   .0664832     2.00   0.046     .0
> 022117                                                                       
>           .2630719
  Navarra (Comunidad Foral de)  |  -.2021894   .0911277    -2.22   0.027    -.3
> 809682                                                                       
>          -.0234105
                    País Vasco  |  -.1195479   .0887344    -1.35   0.178    -.2
> 936314                                                                       
>           .0545356
                    Rioja (La)  |  -.0717746   .1053897    -0.68   0.496    -.2
> 785333                                                                       
>           .1349842
    Ceuta (Ciudad Autónoma de)  |   .2453008   .0872701     2.81   0.005       
> .07409                                                                       
>           .4165116
  Melilla (Ciudad Autónoma de)  |    .112668   .1156438     0.97   0.330    -.1
> 142079                                                                       
>           .3395438
                                |
                          _cons |   .9318536   .1491242     6.25   0.000     .6
> 392944                                                                       
>           1.224413
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,772
                                                F(1, 1770)        =      10.62
                                                Prob > F          =     0.0011
                                                R-squared         =     0.0061
                                                Root MSE          =     .49469

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1119754   .0343661     3.26   0.001      .044573    .1793777
       _cons |   .4208115   .0126368    33.30   0.000     .3960269    .4455962
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,219
                                                F(41, 1176)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2157
                                                Root MSE          =     .45057

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0949424   .0356312     2.66   0.008     .0
> 250345                                                                       
>           .1648503
                         female |  -.0226397    .027848    -0.81   0.416    -.0
> 772771                                                                       
>           .0319977
                                |
                         income |
         Menos o igual a 300 €  |  -.0438937   .0866971    -0.51   0.613    -.2
> 139919                                                                       
>           .1262045
                De 301 a 600 €  |  -.0109203    .061469    -0.18   0.859    -.1
> 315216                                                                       
>           .1096809
                De 601 a 900 €  |  -.0405931   .0475101    -0.85   0.393    -.1
> 338072                                                                       
>            .052621
              De 901 a 1.200 €  |  -.0602595   .0456941    -1.32   0.188    -.1
> 499106                                                                       
>           .0293917
            De 1.201 a 1.800 €  |  -.0345161   .0487765    -0.71   0.479    -.1
> 302148                                                                       
>           .0611826
            De 1.801 a 2.400 €  |   .0076298   .0591814     0.13   0.897    -.1
> 084831                                                                       
>           .1237426
            De 2.401 a 3.000 €  |  -.0170365   .0831878    -0.20   0.838    -.1
> 802497                                                                       
>           .1461767
            De 3.001 a 4.500 €  |   .1286993   .1145688     1.12   0.262    -.0
> 960828                                                                       
>           .3534814
            De 4.501 a 6.000 €  |  -.6555693   .0814145    -8.05   0.000    -.8
> 153033                                                                       
>          -.4958353
                Más de 6.000 €  |   .0187231   .2117325     0.09   0.930    -.3
> 966926                                                                       
>           .4341388
                                |
                            age |   .0000751   .0049444     0.02   0.988    -.0
> 096257                                                                       
>            .009776
                         age_sq |  -.0000277   .0000515    -0.54   0.590    -.0
> 001288                                                                       
>           .0000733
                                |
                      education |
                      Primaria  |  -.0795305   .1166409    -0.68   0.495    -.3
> 083781                                                                       
>           .1493171
           Secundaria 1ª etapa  |  -.1702828   .1185209    -1.44   0.151    -.4
> 028188                                                                       
>           .0622532
           Secundaria 2ª etapa  |  -.2066246   .1201931    -1.72   0.086    -.4
> 424415                                                                       
>           .0291923
                          F.P.  |  -.1207302   .1199005    -1.01   0.314    -.3
> 559731                                                                       
>           .1145126
                    Superiores  |  -.1406936    .121251    -1.16   0.246     -.
> 378586                                                                       
>           .0971988
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0301799   .0636215     0.47   0.635    -.0
> 946445                                                                       
>           .1550043
    10.001 a 50.000 habitantes  |  -.1054063   .0629326    -1.67   0.094     -.
> 228879                                                                       
>           .0180663
   50.001 a 100.000 habitantes  |  -.1536819   .0691532    -2.22   0.026    -.2
> 893593                                                                       
>          -.0180045
  100.001 a 400.000 habitantes  |  -.2209995   .0645257    -3.42   0.001     -.
> 347598                                                                       
>          -.0944011
400.001 a 1.000.000 habitantes  |  -.3624883   .0709257    -5.11   0.000    -.5
> 016434                                                                       
>          -.2233332
   Más de 1.000.000 habitantes  |  -.1797177   .0820779    -2.19   0.029    -.3
> 407532                                                                       
>          -.0186822
                                |
                           CCAA |
                        Aragón  |  -.0171891   .0696233    -0.25   0.805    -.1
> 537887                                                                       
>           .1194106
      Asturias (Principado de)  |  -.2218191   .0729058    -3.04   0.002     -.
> 364859                                                                       
>          -.0787791
               Balears (Illes)  |   -.186584   .0779774    -2.39   0.017    -.3
> 395743                                                                       
>          -.0335936
                      Canarias  |   .3733143   .0542976     6.88   0.000     .2
> 667833                                                                       
>           .4798453
                     Cantabria  |  -.0597981    .068707    -0.87   0.384    -.1
> 946001                                                                       
>            .075004
            Castilla-La Mancha  |   .0036031   .0710522     0.05   0.960       
> -.1358                                                                       
>           .1430063
               Castilla y León  |   .0509235   .0719009     0.71   0.479    -.0
> 901448                                                                       
>           .1919918
          Comunitat Valenciana  |  -.0806545   .0545649    -1.48   0.140    -.1
> 877099                                                                       
>           .0264008
                   Extremadura  |    .160148   .0623087     2.57   0.010     .0
> 378993                                                                       
>           .2823967
                       Galicia  |  -.0307222   .0725939    -0.42   0.672    -.1
> 731502                                                                       
>           .1117058
         Madrid (Comunidad de)  |  -.4069234   .0507393    -8.02   0.000     -.
> 506473                                                                       
>          -.3073737
            Murcia (Región de)  |   .1328329   .0661101     2.01   0.045      .
> 003126                                                                       
>           .2625399
  Navarra (Comunidad Foral de)  |  -.2070001   .0908943    -2.28   0.023    -.3
> 853331                                                                       
>           -.028667
                    País Vasco  |  -.1136827   .0890557    -1.28   0.202    -.2
> 884084                                                                       
>           .0610431
                    Rioja (La)  |  -.0579514   .1052127    -0.55   0.582     -.
> 264377                                                                       
>           .1484741
    Ceuta (Ciudad Autónoma de)  |   .2530203   .0873845     2.90   0.004     .0
> 815734                                                                       
>           .4244672
  Melilla (Ciudad Autónoma de)  |    .125008    .115173     1.09   0.278    -.1
> 009595                                                                       
>           .3509755
                                |
                          _cons |   .9429586   .1565331     6.02   0.000     .6
> 358431                                                                       
>           1.250074
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,585
                                                F(1, 1583)        =       3.66
                                                Prob > F          =     0.0560
                                                R-squared         =     0.0023
                                                Root MSE          =     .49974

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .0658009   .0344039     1.91   0.056    -.0016811    .1332829
       _cons |   .4906507   .0136805    35.86   0.000     .4638169    .5174845
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,231
                                                F(42, 1188)       =      20.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2692
                                                Root MSE          =     .43467

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1061399   .0356579     2.98   0.003     .0
> 361804                                                                       
>           .1760994
                         female |  -.0111724   .0270716    -0.41   0.680    -.0
> 642859                                                                       
>            .041941
                                |
                         income |
         Menos o igual a 300 €  |   .0677789   .0970015     0.70   0.485    -.1
> 225344                                                                       
>           .2580922
                De 301 a 600 €  |   .0558578   .0584535     0.96   0.339    -.0
> 588259                                                                       
>           .1705414
                De 601 a 900 €  |  -.0323555   .0460688    -0.70   0.483    -.1
> 227407                                                                       
>           .0580298
              De 901 a 1.200 €  |  -.0106506   .0437771    -0.24   0.808    -.0
> 965397                                                                       
>           .0752384
            De 1.201 a 1.800 €  |   .0040309   .0461905     0.09   0.930    -.0
> 865931                                                                       
>           .0946549
            De 1.801 a 2.400 €  |   .0369969   .0549496     0.67   0.501    -.0
> 708122                                                                       
>           .1448061
            De 2.401 a 3.000 €  |  -.0009398    .075375    -0.01   0.990    -.1
> 488228                                                                       
>           .1469431
            De 3.001 a 4.500 €  |   .1566595   .1154458     1.36   0.175    -.0
> 698408                                                                       
>           .3831599
            De 4.501 a 6.000 €  |  -.4124089   .1689079    -2.44   0.015    -.7
> 437998                                                                       
>          -.0810179
                Más de 6.000 €  |  -.0681666   .2217799    -0.31   0.759    -.5
> 032906                                                                       
>           .3669574
                                |
                            age |  -.0010706     .00472    -0.23   0.821     -.
> 010331                                                                       
>           .0081898
                         age_sq |  -9.21e-06   .0000492    -0.19   0.852    -.0
> 001058                                                                       
>           .0000874
                                |
                      education |
                      Primaria  |  -.0603138    .105369    -0.57   0.567    -.2
> 670439                                                                       
>           .1464164
           Secundaria 1ª etapa  |  -.1859363   .1065271    -1.75   0.081    -.3
> 949384                                                                       
>           .0230659
           Secundaria 2ª etapa  |  -.1791511   .1081878    -1.66   0.098    -.3
> 914116                                                                       
>           .0331094
                          F.P.  |  -.0995892    .107495    -0.93   0.354    -.3
> 104905                                                                       
>            .111312
                    Superiores  |  -.1077309   .1086636    -0.99   0.322    -.3
> 209248                                                                       
>           .1054629
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0128485   .0608414    -0.21   0.833     -.
> 132217                                                                       
>           .1065201
    10.001 a 50.000 habitantes  |  -.1316762   .0590823    -2.23   0.026    -.2
> 475936                                                                       
>          -.0157588
   50.001 a 100.000 habitantes  |  -.2244018   .0659802    -3.40   0.001    -.3
> 538525                                                                       
>          -.0949511
  100.001 a 400.000 habitantes  |  -.2516094   .0608374    -4.14   0.000    -.3
> 709701                                                                       
>          -.1322486
400.001 a 1.000.000 habitantes  |  -.3753964    .073206    -5.13   0.000    -.5
> 190238                                                                       
>           -.231769
   Más de 1.000.000 habitantes  |  -.2698941   .0646873    -4.17   0.000     -.
> 396808                                                                       
>          -.1429801
                                |
                           CCAA |
                        Aragón  |  -.0443788   .0701359    -0.63   0.527    -.1
> 819828                                                                       
>           .0932252
      Asturias (Principado de)  |  -.2199862   .0732487    -3.00   0.003    -.3
> 636975                                                                       
>          -.0762748
               Balears (Illes)  |  -.2160477   .0787224    -2.74   0.006    -.3
> 704982                                                                       
>          -.0615972
                      Canarias  |   .3630697   .0550127     6.60   0.000     .2
> 551368                                                                       
>           .4710026
                     Cantabria  |  -.0690588   .0688193    -1.00   0.316    -.2
> 040798                                                                       
>           .0659622
            Castilla-La Mancha  |   .0038871   .0708247     0.05   0.956    -.1
> 350684                                                                       
>           .1428425
               Castilla y León  |   .0430638   .0711348     0.61   0.545    -.0
> 965001                                                                       
>           .1826276
                      Cataluña  |  -.4462654   .0484489    -9.21   0.000    -.5
> 413204                                                                       
>          -.3512104
                   Extremadura  |   .1463407   .0609126     2.40   0.016     .0
> 268324                                                                       
>           .2658489
                       Galicia  |  -.0362072   .0719712    -0.50   0.615     -.
> 177412                                                                       
>           .1049977
         Madrid (Comunidad de)  |  -.3927278    .047484    -8.27   0.000    -.4
> 858896                                                                       
>           -.299566
            Murcia (Región de)  |   .1202507    .066323     1.81   0.070    -.0
> 098725                                                                       
>           .2503739
  Navarra (Comunidad Foral de)  |  -.2219099   .0910607    -2.44   0.015    -.4
> 005676                                                                       
>          -.0432522
                    País Vasco  |  -.1225487   .0882917    -1.39   0.165    -.2
> 957739                                                                       
>           .0506764
                    Rioja (La)  |  -.0716443   .1056358    -0.68   0.498    -.2
> 788978                                                                       
>           .1356092
    Ceuta (Ciudad Autónoma de)  |   .2920295   .0893201     3.27   0.001     .1
> 167867                                                                       
>           .4672722
  Melilla (Ciudad Autónoma de)  |   .1542586   .1159715     1.33   0.184    -.0
> 732731                                                                       
>           .3817903
                                |
                          _cons |   .9380532   .1480007     6.34   0.000     .6
> 476814                                                                       
>           1.228425
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,706
                                                F(1, 1704)        =      10.17
                                                Prob > F          =     0.0015
                                                R-squared         =     0.0060
                                                Root MSE          =     .49521

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1108886   .0347663     3.19   0.001     .0426994    .1790778
       _cons |   .4246762   .0129129    32.89   0.000     .3993493    .4500031
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,291
                                                F(41, 1248)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2391
                                                Root MSE          =     .44228

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0886735   .0365725     2.42   0.015     .0
> 169232                                                                       
>           .1604238
                         female |  -.0161217   .0268579    -0.60   0.548    -.0
> 688134                                                                       
>             .03657
                                |
                         income |
         Menos o igual a 300 €  |   .0046223   .0965992     0.05   0.962    -.1
> 848926                                                                       
>           .1941371
                De 301 a 600 €  |  -.0009543   .0594583    -0.02   0.987    -.1
> 176036                                                                       
>            .115695
                De 601 a 900 €  |  -.0422093   .0463866    -0.91   0.363    -.1
> 332137                                                                       
>           .0487951
              De 901 a 1.200 €  |  -.0508867   .0439613    -1.16   0.247    -.1
> 371328                                                                       
>           .0353595
            De 1.201 a 1.800 €  |  -.0318779   .0462092    -0.69   0.490    -.1
> 225341                                                                       
>           .0587784
            De 1.801 a 2.400 €  |   .0017912   .0541896     0.03   0.974    -.1
> 045217                                                                       
>            .108104
            De 2.401 a 3.000 €  |  -.0408705   .0745599    -0.55   0.584    -.1
> 871471                                                                       
>           .1054061
            De 3.001 a 4.500 €  |    .144433   .1098922     1.31   0.189    -.0
> 711609                                                                       
>           .3600268
            De 4.501 a 6.000 €  |  -.1850405   .0570354    -3.24   0.001    -.2
> 969364                                                                       
>          -.0731446
                Más de 6.000 €  |   .0056606   .2098508     0.03   0.978    -.4
> 060386                                                                       
>           .4173599
                                |
                            age |  -.0003618   .0045989    -0.08   0.937    -.0
> 093842                                                                       
>           .0086606
                         age_sq |  -.0000189   .0000477    -0.40   0.692    -.0
> 001126                                                                       
>           .0000747
                                |
                      education |
                      Primaria  |  -.1149666    .103061    -1.12   0.265    -.3
> 171586                                                                       
>           .0872253
           Secundaria 1ª etapa  |  -.1810628   .1034466    -1.75   0.080    -.3
> 840113                                                                       
>           .0218856
           Secundaria 2ª etapa  |  -.2078436   .1048315    -1.98   0.048     -.
> 413509                                                                       
>          -.0021782
                          F.P.  |  -.1379849   .1041158    -1.33   0.185    -.3
> 422462                                                                       
>           .0662765
                    Superiores  |  -.1521425   .1054238    -1.44   0.149    -.3
> 589699                                                                       
>           .0546848
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0346877   .0670324     0.52   0.605    -.0
> 968208                                                                       
>           .1661963
    10.001 a 50.000 habitantes  |  -.1149658   .0653516    -1.76   0.079    -.2
> 431769                                                                       
>           .0132452
   50.001 a 100.000 habitantes  |  -.1263864   .0710311    -1.78   0.075    -.2
> 657399                                                                       
>           .0129672
  100.001 a 400.000 habitantes  |  -.2072568   .0673704    -3.08   0.002    -.3
> 394285                                                                       
>           -.075085
400.001 a 1.000.000 habitantes  |   -.362214    .073108    -4.95   0.000    -.5
> 056421                                                                       
>          -.2187859
   Más de 1.000.000 habitantes  |  -.2160757   .0699618    -3.09   0.002    -.3
> 533315                                                                       
>          -.0788199
                                |
                           CCAA |
                        Aragón  |  -.0151828   .0693349    -0.22   0.827    -.1
> 512086                                                                       
>            .120843
      Asturias (Principado de)  |  -.2267632   .0731675    -3.10   0.002    -.3
> 703081                                                                       
>          -.0832183
               Balears (Illes)  |  -.1795808   .0777703    -2.31   0.021    -.3
> 321558                                                                       
>          -.0270058
                      Canarias  |   .3719087   .0540858     6.88   0.000     .2
> 657996                                                                       
>           .4780178
                     Cantabria  |  -.0557857   .0686632    -0.81   0.417    -.1
> 904938                                                                       
>           .0789224
            Castilla-La Mancha  |  -.0014139    .070654    -0.02   0.984    -.1
> 400277                                                                       
>              .1372
               Castilla y León  |   .0508133   .0718955     0.71   0.480    -.0
> 902361                                                                       
>           .1918628
                      Cataluña  |  -.4395739   .0485073    -9.06   0.000    -.5
> 347387                                                                       
>           -.344409
          Comunitat Valenciana  |   -.080327    .054333    -1.48   0.140    -.1
> 869211                                                                       
>           .0262671
                       Galicia  |  -.0315033   .0726876    -0.43   0.665    -.1
> 741067                                                                       
>           .1111002
         Madrid (Comunidad de)  |  -.3988444   .0471939    -8.45   0.000    -.4
> 914325                                                                       
>          -.3062562
            Murcia (Región de)  |   .1384191   .0661897     2.09   0.037     .0
> 085637                                                                       
>           .2682744
  Navarra (Comunidad Foral de)  |  -.2004815   .0916251    -2.19   0.029    -.3
> 802377                                                                       
>          -.0207253
                    País Vasco  |  -.1120401   .0889481    -1.26   0.208    -.2
> 865444                                                                       
>           .0624643
                    Rioja (La)  |  -.0621275    .105638    -0.59   0.557    -.2
> 693751                                                                       
>           .1451201
    Ceuta (Ciudad Autónoma de)  |   .2281942    .087265     2.61   0.009     .0
> 569919                                                                       
>           .3993965
  Melilla (Ciudad Autónoma de)  |    .103027    .115148     0.89   0.371    -.1
> 228779                                                                       
>            .328932
                                |
                          _cons |   .9453892   .1464296     6.46   0.000     .6
> 581139                                                                       
>           1.232665
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,775
                                                F(1, 1773)        =       9.28
                                                Prob > F          =     0.0024
                                                R-squared         =     0.0053
                                                Root MSE          =     .49402

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |    .105136   .0345117     3.05   0.002     .0374481     .172824
       _cons |   .4155251   .0125938    32.99   0.000     .3908249    .4402253
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,294
                                                F(42, 1251)       =      20.18
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2593
                                                Root MSE          =     .43699

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |    .113872   .0347571     3.28   0.001     .0
> 456834                                                                       
>           .1820606
                         female |  -.0130444   .0264253    -0.49   0.622    -.0
> 648871                                                                       
>           .0387983
                                |
                         income |
         Menos o igual a 300 €  |   .0093725   .0914776     0.10   0.918    -.1
> 700939                                                                       
>           .1888389
                De 301 a 600 €  |   -.005717   .0582536    -0.10   0.922    -.1
> 200025                                                                       
>           .1085686
                De 601 a 900 €  |  -.0436121   .0455108    -0.96   0.338    -.1
> 328981                                                                       
>           .0456739
              De 901 a 1.200 €  |    -.05649   .0433717    -1.30   0.193    -.1
> 415793                                                                       
>           .0285993
            De 1.201 a 1.800 €  |  -.0261622   .0454918    -0.58   0.565    -.1
> 154108                                                                       
>           .0630864
            De 1.801 a 2.400 €  |   .0005122   .0537471     0.01   0.992    -.1
> 049322                                                                       
>           .1059566
            De 2.401 a 3.000 €  |  -.0473026   .0733867    -0.64   0.519    -.1
> 912773                                                                       
>            .096672
            De 3.001 a 4.500 €  |   .1315177   .1126755     1.17   0.243     -.
> 089536                                                                       
>           .3525714
            De 4.501 a 6.000 €  |  -.4159815    .174879    -2.38   0.018    -.7
> 590699                                                                       
>          -.0728931
                Más de 6.000 €  |   .0081279   .2104057     0.04   0.969    -.4
> 046591                                                                       
>           .4209148
                                |
                            age |  -.0009559   .0046658    -0.20   0.838    -.0
> 101096                                                                       
>           .0081977
                         age_sq |  -.0000132   .0000488    -0.27   0.786    -.0
> 001089                                                                       
>           .0000824
                                |
                      education |
                      Primaria  |  -.0413368   .1132638    -0.36   0.715    -.2
> 635447                                                                       
>           .1808712
           Secundaria 1ª etapa  |  -.1017959   .1142119    -0.89   0.373    -.3
> 258638                                                                       
>            .122272
           Secundaria 2ª etapa  |  -.1378373   .1159315    -1.19   0.235    -.3
> 652788                                                                       
>           .0896043
                          F.P.  |  -.0446616    .115084    -0.39   0.698    -.2
> 704404                                                                       
>           .1811173
                    Superiores  |  -.0810833   .1166736    -0.69   0.487    -.3
> 099808                                                                       
>           .1478141
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0063537   .0611878    -0.10   0.917    -.1
> 263958                                                                       
>           .1136884
    10.001 a 50.000 habitantes  |  -.1335447   .0593809    -2.25   0.025    -.2
> 500419                                                                       
>          -.0170474
   50.001 a 100.000 habitantes  |  -.1555797    .065463    -2.38   0.018    -.2
> 840091                                                                       
>          -.0271503
  100.001 a 400.000 habitantes  |  -.2300914   .0609577    -3.77   0.000     -.
> 349682                                                                       
>          -.1105007
400.001 a 1.000.000 habitantes  |  -.3853508   .0686166    -5.62   0.000    -.5
> 199672                                                                       
>          -.2507344
   Más de 1.000.000 habitantes  |  -.2407975   .0648111    -3.72   0.000    -.3
> 679479                                                                       
>          -.1136472
                                |
                           CCAA |
                        Aragón  |  -.0212967   .0687659    -0.31   0.757    -.1
> 562059                                                                       
>           .1136125
      Asturias (Principado de)  |  -.2259773   .0731591    -3.09   0.002    -.3
> 695053                                                                       
>          -.0824492
               Balears (Illes)  |  -.1791034   .0779851    -2.30   0.022    -.3
> 320994                                                                       
>          -.0261074
                      Canarias  |   .3682757   .0541328     6.80   0.000     .2
> 620747                                                                       
>           .4744768
                     Cantabria  |  -.0612553   .0683834    -0.90   0.371     -.
> 195414                                                                       
>           .0729035
            Castilla-La Mancha  |  -.0041214   .0707723    -0.06   0.954     -.
> 142967                                                                       
>           .1347241
               Castilla y León  |   .0451358   .0715607     0.63   0.528    -.0
> 952565                                                                       
>            .185528
                      Cataluña  |  -.4404674   .0482034    -9.14   0.000    -.5
> 350357                                                                       
>           -.345899
          Comunitat Valenciana  |  -.0829751   .0541972    -1.53   0.126    -.1
> 893025                                                                       
>           .0233523
                   Extremadura  |   .1505246   .0616222     2.44   0.015     .0
> 296303                                                                       
>           .2714189
         Madrid (Comunidad de)  |  -.4006105   .0473354    -8.46   0.000     -.
> 493476                                                                       
>          -.3077451
            Murcia (Región de)  |   .1331386   .0663465     2.01   0.045     .0
> 029759                                                                       
>           .2633013
  Navarra (Comunidad Foral de)  |  -.1959197   .0917769    -2.13   0.033    -.3
> 759734                                                                       
>           -.015866
                    País Vasco  |  -.1171077   .0882686    -1.33   0.185    -.2
> 902785                                                                       
>           .0560631
                    Rioja (La)  |  -.0698894   .1057581    -0.66   0.509    -.2
> 773722                                                                       
>           .1375933
    Ceuta (Ciudad Autónoma de)  |   .2242808   .0871566     2.57   0.010     .0
> 532915                                                                       
>             .39527
  Melilla (Ciudad Autónoma de)  |   .1016178   .1149753     0.88   0.377     -.
> 123948                                                                       
>           .3271835
                                |
                          _cons |   .9049066   .1532215     5.91   0.000     .6
> 043072                                                                       
>           1.205506
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,764
                                                F(1, 1762)        =      15.50
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0088
                                                Root MSE          =      .4944

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1337548   .0339759     3.94   0.000     .0671175    .2003921
       _cons |    .420462   .0126895    33.13   0.000      .395574    .4453501
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,204
                                                F(42, 1161)       =      47.34
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2150
                                                Root MSE          =      .4508

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .1143505   .0390139     2.93   0.003     .0
> 378048                                                                       
>           .1908962
                         female |  -.0062372   .0283627    -0.22   0.826    -.0
> 618852                                                                       
>           .0494107
                                |
                         income |
         Menos o igual a 300 €  |  -.0317325   .0933114    -0.34   0.734    -.2
> 148103                                                                       
>           .1513452
                De 301 a 600 €  |  -.0272454   .0579741    -0.47   0.638    -.1
> 409911                                                                       
>           .0865004
                De 601 a 900 €  |  -.0315145    .047747    -0.66   0.509    -.1
> 251946                                                                       
>           .0621656
              De 901 a 1.200 €  |  -.0553604   .0461976    -1.20   0.231    -.1
> 460004                                                                       
>           .0352797
            De 1.201 a 1.800 €  |  -.0220372   .0490546    -0.45   0.653    -.1
> 182828                                                                       
>           .0742085
            De 1.801 a 2.400 €  |   .0180015   .0583183     0.31   0.758    -.0
> 964196                                                                       
>           .1324226
            De 2.401 a 3.000 €  |   -.003911   .0846009    -0.05   0.963    -.1
> 698988                                                                       
>           .1620768
            De 3.001 a 4.500 €  |   .0708107   .1137266     0.62   0.534    -.1
> 523219                                                                       
>           .2939433
            De 4.501 a 6.000 €  |  -.4274972   .1721034    -2.48   0.013    -.7
> 651656                                                                       
>          -.0898287
                Más de 6.000 €  |   .1335382     .29531     0.45   0.651    -.4
> 458629                                                                       
>           .7129393
                                |
                            age |  -.0020579   .0048535    -0.42   0.672    -.0
> 115806                                                                       
>           .0074648
                         age_sq |  -6.28e-07   .0000506    -0.01   0.990    -.0
> 000999                                                                       
>           .0000987
                                |
                      education |
                      Primaria  |  -.0510914    .107884    -0.47   0.636    -.2
> 627609                                                                       
>            .160578
           Secundaria 1ª etapa  |  -.1234183   .1089431    -1.13   0.258    -.3
> 371658                                                                       
>           .0903291
           Secundaria 2ª etapa  |   -.170155    .111238    -1.53   0.126     -.
> 388405                                                                       
>            .048095
                          F.P.  |  -.0702151   .1101797    -0.64   0.524    -.2
> 863887                                                                       
>           .1459585
                    Superiores  |  -.1006937   .1114884    -0.90   0.367     -.
> 319435                                                                       
>           .1180477
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0029752   .0604515    -0.05   0.961    -.1
> 215815                                                                       
>           .1156312
    10.001 a 50.000 habitantes  |   -.131564   .0587752    -2.24   0.025    -.2
> 468815                                                                       
>          -.0162466
   50.001 a 100.000 habitantes  |  -.1814705   .0672767    -2.70   0.007    -.3
> 134681                                                                       
>           -.049473
  100.001 a 400.000 habitantes  |   -.224798   .0619276    -3.63   0.000    -.3
> 463005                                                                       
>          -.1032955
400.001 a 1.000.000 habitantes  |   -.385789    .068312    -5.65   0.000    -.5
> 198178                                                                       
>          -.2517603
   Más de 1.000.000 habitantes  |  -.3060877   .0658834    -4.65   0.000    -.4
> 353515                                                                       
>          -.1768238
                                |
                           CCAA |
                        Aragón  |   -.020867   .0691635    -0.30   0.763    -.1
> 565665                                                                       
>           .1148324
      Asturias (Principado de)  |  -.2290475   .0730716    -3.13   0.002    -.3
> 724147                                                                       
>          -.0856804
               Balears (Illes)  |  -.1847941   .0777167    -2.38   0.018    -.3
> 372751                                                                       
>          -.0323131
                      Canarias  |   .3675846   .0541176     6.79   0.000     .2
> 614052                                                                       
>           .4737639
                     Cantabria  |  -.0650681    .068602    -0.95   0.343    -.1
> 996658                                                                       
>           .0695296
            Castilla-La Mancha  |   .0007925   .0710299     0.01   0.991    -.1
> 385688                                                                       
>           .1401539
               Castilla y León  |   .0416436   .0716158     0.58   0.561    -.0
> 988673                                                                       
>           .1821544
                      Cataluña  |  -.4281247   .0520397    -8.23   0.000    -.5
> 302271                                                                       
>          -.3260222
          Comunitat Valenciana  |  -.0820522   .0544731    -1.51   0.132    -.1
> 889289                                                                       
>           .0248244
                   Extremadura  |   .1534532    .061079     2.51   0.012     .0
> 336157                                                                       
>           .2732908
                       Galicia  |  -.0297205   .0728947    -0.41   0.684    -.1
> 727407                                                                       
>           .1132996
            Murcia (Región de)  |    .130079   .0663958     1.96   0.050    -.0
> 001902                                                                       
>           .2603483
  Navarra (Comunidad Foral de)  |  -.2004497   .0916752    -2.19   0.029    -.3
> 803174                                                                       
>           -.020582
                    País Vasco  |  -.1235401   .0893363    -1.38   0.167    -.2
> 988187                                                                       
>           .0517386
                    Rioja (La)  |  -.0685249   .1061136    -0.65   0.519    -.2
> 767207                                                                       
>           .1396709
    Ceuta (Ciudad Autónoma de)  |   .2501716   .0890881     2.81   0.005     .0
> 753798                                                                       
>           .4249633
  Melilla (Ciudad Autónoma de)  |   .1296798   .1173857     1.10   0.270    -.1
> 006321                                                                       
>           .3599917
                                |
                          _cons |   .9439456   .1518845     6.21   0.000     .6
> 459467                                                                       
>           1.241945
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,620
                                                F(1, 1618)        =      21.86
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0127
                                                Root MSE          =     .49694

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |    .166403   .0355907     4.68   0.000     .0965942    .2362118
       _cons |   .4644381    .013309    34.90   0.000     .4383335    .4905427
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,289
                                                F(42, 1246)       =      19.88
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2541
                                                Root MSE          =     .43832

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0944981   .0360398     2.62   0.009     .0
> 237927                                                                       
>           .1652035
                         female |  -.0231089   .0266175    -0.87   0.385     -.
> 075329                                                                       
>           .0291111
                                |
                         income |
         Menos o igual a 300 €  |   .0208245   .0905116     0.23   0.818    -.1
> 567474                                                                       
>           .1983965
                De 301 a 600 €  |  -.0026999   .0581339    -0.05   0.963    -.1
> 167511                                                                       
>           .1113513
                De 601 a 900 €  |  -.0189589   .0459357    -0.41   0.680    -.1
> 090788                                                                       
>            .071161
              De 901 a 1.200 €  |  -.0400313    .043465    -0.92   0.357     -.
> 125304                                                                       
>           .0452415
            De 1.201 a 1.800 €  |  -.0161868   .0461135    -0.35   0.726    -.1
> 066556                                                                       
>           .0742819
            De 1.801 a 2.400 €  |   .0062983   .0543288     0.12   0.908    -.1
> 002878                                                                       
>           .1128844
            De 2.401 a 3.000 €  |  -.0393217   .0737034    -0.53   0.594    -.1
> 839182                                                                       
>           .1052749
            De 3.001 a 4.500 €  |   .1894936   .1143065     1.66   0.098    -.0
> 347608                                                                       
>           .4137481
            De 4.501 a 6.000 €  |  -.4216783   .1872585    -2.25   0.025    -.7
> 890551                                                                       
>          -.0543015
                Más de 6.000 €  |  -.0755676   .2210598    -0.34   0.733    -.5
> 092581                                                                       
>           .3581229
                                |
                            age |  -.0017414   .0046224    -0.38   0.706    -.0
> 108098                                                                       
>           .0073271
                         age_sq |  -5.30e-06    .000048    -0.11   0.912    -.0
> 000995                                                                       
>            .000089
                                |
                      education |
                      Primaria  |  -.0444999   .1092061    -0.41   0.684    -.2
> 587481                                                                       
>           .1697482
           Secundaria 1ª etapa  |  -.1204493   .1098927    -1.10   0.273    -.3
> 360444                                                                       
>           .0951459
           Secundaria 2ª etapa  |  -.1458212   .1114325    -1.31   0.191    -.3
> 644372                                                                       
>           .0727949
                          F.P.  |  -.0577872   .1108317    -0.52   0.602    -.2
> 752245                                                                       
>           .1596501
                    Superiores  |  -.0816732    .112107    -0.73   0.466    -.3
> 016125                                                                       
>           .1382661
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0013516   .0600179     0.02   0.982    -.1
> 163957                                                                       
>            .119099
    10.001 a 50.000 habitantes  |  -.1329249   .0584239    -2.28   0.023    -.2
> 475451                                                                       
>          -.0183048
   50.001 a 100.000 habitantes  |  -.1776942   .0646652    -2.75   0.006     -.
> 304559                                                                       
>          -.0508295
  100.001 a 400.000 habitantes  |  -.2072365   .0599984    -3.45   0.001    -.3
> 249455                                                                       
>          -.0895275
400.001 a 1.000.000 habitantes  |  -.4154163    .069523    -5.98   0.000    -.5
> 518114                                                                       
>          -.2790211
   Más de 1.000.000 habitantes  |  -.2385748   .0637185    -3.74   0.000    -.3
> 635823                                                                       
>          -.1135674
                                |
                           CCAA |
                        Aragón  |  -.0160403   .0689922    -0.23   0.816    -.1
> 513941                                                                       
>           .1193134
      Asturias (Principado de)  |  -.2399418   .0723653    -3.32   0.001    -.3
> 819132                                                                       
>          -.0979705
               Balears (Illes)  |  -.1724229   .0785095    -2.20   0.028    -.3
> 264482                                                                       
>          -.0183976
                      Canarias  |   .3553007   .0544171     6.53   0.000     .2
> 485414                                                                       
>             .46206
                     Cantabria  |  -.0693913   .0690646    -1.00   0.315    -.2
> 048871                                                                       
>           .0661046
            Castilla-La Mancha  |  -.0055144   .0711803    -0.08   0.938    -.1
> 451609                                                                       
>           .1341322
               Castilla y León  |   .0335012    .071451     0.47   0.639    -.1
> 066763                                                                       
>           .1736788
                      Cataluña  |  -.4512942   .0481623    -9.37   0.000    -.5
> 457824                                                                       
>           -.356806
          Comunitat Valenciana  |  -.0801639   .0543436    -1.48   0.140    -.1
> 867791                                                                       
>           .0264512
                   Extremadura  |   .1443287   .0609851     2.37   0.018     .0
> 246839                                                                       
>           .2639734
                       Galicia  |  -.0376488    .072302    -0.52   0.603    -.1
> 794959                                                                       
>           .1041984
         Madrid (Comunidad de)  |  -.4075365   .0473701    -8.60   0.000    -.5
> 004705                                                                       
>          -.3146025
  Navarra (Comunidad Foral de)  |  -.2136019   .0910912    -2.34   0.019    -.3
> 923109                                                                       
>          -.0348929
                    País Vasco  |  -.1332203   .0895993    -1.49   0.137    -.3
> 090025                                                                       
>           .0425618
                    Rioja (La)  |  -.0874831   .1068839    -0.82   0.413    -.2
> 971753                                                                       
>           .1222091
    Ceuta (Ciudad Autónoma de)  |   .2512361   .0878727     2.86   0.004     .0
> 788414                                                                       
>           .4236308
  Melilla (Ciudad Autónoma de)  |   .1224279   .1152283     1.06   0.288    -.1
> 036351                                                                       
>           .3484908
                                |
                          _cons |   .9314817   .1502767     6.20   0.000     .6
> 366583                                                                       
>           1.226305
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,773
                                                F(1, 1771)        =       9.96
                                                Prob > F          =     0.0016
                                                R-squared         =     0.0057
                                                Root MSE          =     .49438

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1083369   .0343234     3.16   0.002     .0410182    .1756556
       _cons |   .4181937   .0126259    33.12   0.000     .3934305    .4429569
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,321
                                                F(42, 1278)       =      20.25
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2549
                                                Root MSE          =     .43837

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0986576   .0348963     2.83   0.005     .0
> 301973                                                                       
>           .1671179
                         female |  -.0158829   .0261366    -0.61   0.544    -.0
> 671582                                                                       
>           .0353925
                                |
                         income |
         Menos o igual a 300 €  |  -.0115516   .0900129    -0.13   0.898    -.1
> 881409                                                                       
>           .1650377
                De 301 a 600 €  |   .0059069   .0570327     0.10   0.918    -.1
> 059811                                                                       
>           .1177949
                De 601 a 900 €  |  -.0430475   .0449298    -0.96   0.338    -.1
> 311917                                                                       
>           .0450967
              De 901 a 1.200 €  |  -.0541867   .0427616    -1.27   0.205    -.1
> 380773                                                                       
>           .0297039
            De 1.201 a 1.800 €  |  -.0366451   .0451515    -0.81   0.417    -.1
> 252243                                                                       
>           .0519341
            De 1.801 a 2.400 €  |  -.0151117   .0535924    -0.28   0.778    -.1
> 202504                                                                       
>            .090027
            De 2.401 a 3.000 €  |  -.0612316   .0734903    -0.83   0.405    -.2
> 054064                                                                       
>           .0829433
            De 3.001 a 4.500 €  |   .0972887   .1142946     0.85   0.395     -.
> 126937                                                                       
>           .3215143
            De 4.501 a 6.000 €  |   -.430141    .181321    -2.37   0.018    -.7
> 858605                                                                       
>          -.0744214
                Más de 6.000 €  |   .0136334   .2104343     0.06   0.948    -.3
> 992013                                                                       
>           .4264681
                                |
                            age |   .0004567   .0045451     0.10   0.920      -
> .00846                                                                       
>           .0093734
                         age_sq |  -.0000281   .0000472    -0.59   0.552    -.0
> 001208                                                                       
>           .0000646
                                |
                      education |
                      Primaria  |  -.0946141   .1078669    -0.88   0.381    -.3
> 062297                                                                       
>           .1170015
           Secundaria 1ª etapa  |  -.1621822     .10904    -1.49   0.137    -.3
> 760994                                                                       
>           .0517349
           Secundaria 2ª etapa  |  -.1826506   .1106522    -1.65   0.099    -.3
> 997305                                                                       
>           .0344293
                          F.P.  |  -.1061704   .1098818    -0.97   0.334    -.3
> 217391                                                                       
>           .1093982
                    Superiores  |  -.1278145   .1113403    -1.15   0.251    -.3
> 462444                                                                       
>           .0906155
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    -.02351   .0608868    -0.39   0.699     -.
> 142959                                                                       
>           .0959391
    10.001 a 50.000 habitantes  |  -.1618286   .0593067    -2.73   0.006    -.2
> 781779                                                                       
>          -.0454793
   50.001 a 100.000 habitantes  |  -.2024225   .0653893    -3.10   0.002    -.3
> 307047                                                                       
>          -.0741403
  100.001 a 400.000 habitantes  |  -.2397205   .0610903    -3.92   0.000    -.3
> 595688                                                                       
>          -.1198721
400.001 a 1.000.000 habitantes  |  -.4081399   .0685879    -5.95   0.000    -.5
> 426972                                                                       
>          -.2735826
   Más de 1.000.000 habitantes  |  -.2613731   .0648648    -4.03   0.000    -.3
> 886262                                                                       
>          -.1341199
                                |
                           CCAA |
                        Aragón  |  -.0236041   .0689954    -0.34   0.732    -.1
> 589608                                                                       
>           .1117525
      Asturias (Principado de)  |  -.2293389   .0721638    -3.18   0.002    -.3
> 709114                                                                       
>          -.0877665
               Balears (Illes)  |  -.1798828   .0778829    -2.31   0.021    -.3
> 326752                                                                       
>          -.0270904
                      Canarias  |   .3646033   .0544238     6.70   0.000     .2
> 578336                                                                       
>           .4713731
                     Cantabria  |  -.0634739   .0686675    -0.92   0.355    -.1
> 981872                                                                       
>           .0712394
            Castilla-La Mancha  |   .0031682    .070696     0.04   0.964    -.1
> 355249                                                                       
>           .1418612
               Castilla y León  |   .0416975   .0713083     0.58   0.559    -.0
> 981968                                                                       
>           .1815917
                      Cataluña  |   -.442877   .0481313    -9.20   0.000     -.
> 537302                                                                       
>          -.3484519
          Comunitat Valenciana  |  -.0811887   .0544232    -1.49   0.136    -.1
> 879573                                                                       
>           .0255798
                   Extremadura  |   .1453864   .0614536     2.37   0.018     .0
> 248253                                                                       
>           .2659475
                       Galicia  |  -.0332402    .072475    -0.46   0.647    -.1
> 754233                                                                       
>           .1089429
         Madrid (Comunidad de)  |  -.3990648   .0471959    -8.46   0.000    -.4
> 916547                                                                       
>          -.3064749
            Murcia (Región de)  |   .1360563    .066313     2.05   0.040      .
> 005962                                                                       
>           .2661505
                    País Vasco  |  -.1206448   .0891861    -1.35   0.176    -.2
> 956121                                                                       
>           .0543225
                    Rioja (La)  |   -.076961    .106693    -0.72   0.471    -.2
> 862736                                                                       
>           .1323516
    Ceuta (Ciudad Autónoma de)  |   .2529534    .086849     2.91   0.004      .
> 082571                                                                       
>           .4233357
  Melilla (Ciudad Autónoma de)  |   .1268498   .1148849     1.10   0.270    -.0
> 985339                                                                       
>           .3522335
                                |
                          _cons |   .9580181   .1478322     6.48   0.000     .6
> 679977                                                                       
>           1.248039
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,806
                                                F(1, 1804)        =      12.17
                                                Prob > F          =     0.0005
                                                R-squared         =     0.0068
                                                Root MSE          =     .49526

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1171623   .0335908     3.49   0.000     .0512814    .1830432
       _cons |   .4258065   .0125664    33.88   0.000     .4011603    .4504526
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,317
                                                F(42, 1274)       =      20.85
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2568
                                                Root MSE          =     .43781

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0959962   .0348586     2.75   0.006     .0
> 276096                                                                       
>           .1643828
                         female |  -.0287005   .0262781    -1.09   0.275    -.0
> 802536                                                                       
>           .0228525
                                |
                         income |
         Menos o igual a 300 €  |  -.0079864   .0897144    -0.09   0.929    -.1
> 839907                                                                       
>           .1680179
                De 301 a 600 €  |  -.0225686   .0571279    -0.40   0.693    -.1
> 346437                                                                       
>           .0895065
                De 601 a 900 €  |  -.0280744   .0451811    -0.62   0.534     -.
> 116712                                                                       
>           .0605632
              De 901 a 1.200 €  |   -.053097   .0427374    -1.24   0.214    -.1
> 369404                                                                       
>           .0307463
            De 1.201 a 1.800 €  |  -.0388065   .0453968    -0.85   0.393    -.1
> 278673                                                                       
>           .0502542
            De 1.801 a 2.400 €  |   -.011665   .0537433    -0.22   0.828    -.1
> 171001                                                                       
>           .0937701
            De 2.401 a 3.000 €  |  -.0624015   .0733493    -0.85   0.395    -.2
> 063002                                                                       
>           .0814971
            De 3.001 a 4.500 €  |   .1292255    .110233     1.17   0.241    -.0
> 870328                                                                       
>           .3454837
            De 4.501 a 6.000 €  |  -.4451435   .1862218    -2.39   0.017    -.8
> 104787                                                                       
>          -.0798084
                Más de 6.000 €  |   .0097532   .2136695     0.05   0.964    -.4
> 094294                                                                       
>           .4289359
                                |
                            age |   -.001311   .0046706    -0.28   0.779    -.0
> 104738                                                                       
>           .0078519
                         age_sq |  -8.79e-06   .0000489    -0.18   0.857    -.0
> 001046                                                                       
>           .0000871
                                |
                      education |
                      Primaria  |   -.051692   .1055952    -0.49   0.625    -.2
> 588515                                                                       
>           .1554676
           Secundaria 1ª etapa  |  -.1247637   .1072789    -1.16   0.245    -.3
> 352265                                                                       
>           .0856991
           Secundaria 2ª etapa  |  -.1582169   .1086115    -1.46   0.145     -.
> 371294                                                                       
>           .0548601
                          F.P.  |  -.0927235   .1078426    -0.86   0.390    -.3
> 042921                                                                       
>           .1188451
                    Superiores  |  -.0772962   .1093676    -0.71   0.480    -.2
> 918567                                                                       
>           .1372642
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0066438   .0596079    -0.11   0.911    -.1
> 235841                                                                       
>           .1102966
    10.001 a 50.000 habitantes  |  -.1554259   .0581498    -2.67   0.008    -.2
> 695058                                                                       
>          -.0413461
   50.001 a 100.000 habitantes  |  -.2003288   .0643276    -3.11   0.002    -.3
> 265285                                                                       
>           -.074129
  100.001 a 400.000 habitantes  |  -.2287537    .060057    -3.81   0.000    -.3
> 465752                                                                       
>          -.1109321
400.001 a 1.000.000 habitantes  |  -.4040273   .0677338    -5.96   0.000    -.5
> 369094                                                                       
>          -.2711453
   Más de 1.000.000 habitantes  |  -.2570851   .0636612    -4.04   0.000    -.3
> 819773                                                                       
>          -.1321928
                                |
                           CCAA |
                        Aragón  |  -.0231569    .069233    -0.33   0.738      -
> .15898                                                                       
>           .1126663
      Asturias (Principado de)  |  -.2299921   .0721039    -3.19   0.001    -.3
> 714476                                                                       
>          -.0885367
               Balears (Illes)  |    -.18005    .077356    -2.33   0.020    -.3
> 318092                                                                       
>          -.0282908
                      Canarias  |   .3678045   .0537098     6.85   0.000     .2
> 624351                                                                       
>           .4731738
                     Cantabria  |  -.0654471   .0689664    -0.95   0.343    -.2
> 007474                                                                       
>           .0698531
            Castilla-La Mancha  |   .0043116   .0709135     0.06   0.952    -.1
> 348086                                                                       
>           .1434317
               Castilla y León  |   .0381444   .0711094     0.54   0.592      -
> .10136                                                                       
>           .1776487
                      Cataluña  |  -.4412465   .0482021    -9.15   0.000    -.5
> 358107                                                                       
>          -.3466822
          Comunitat Valenciana  |  -.0791945   .0543528    -1.46   0.145    -.1
> 858254                                                                       
>           .0274364
                   Extremadura  |   .1431602   .0612026     2.34   0.019     .0
> 230913                                                                       
>           .2632291
                       Galicia  |  -.0324352   .0718252    -0.45   0.652    -.1
> 733439                                                                       
>           .1084735
         Madrid (Comunidad de)  |  -.4011792   .0474511    -8.45   0.000    -.4
> 942702                                                                       
>          -.3080882
            Murcia (Región de)  |   .1354226   .0665493     2.03   0.042     .0
> 048642                                                                       
>           .2659809
  Navarra (Comunidad Foral de)  |  -.2110243   .0912659    -2.31   0.021    -.3
> 900722                                                                       
>          -.0319763
                    Rioja (La)  |  -.0776673   .1078026    -0.72   0.471    -.2
> 891575                                                                       
>           .1338229
    Ceuta (Ciudad Autónoma de)  |   .2614176   .0873217     2.99   0.003     .0
> 901075                                                                       
>           .4327277
  Melilla (Ciudad Autónoma de)  |   .1325523   .1145362     1.16   0.247     -.
> 092148                                                                       
>           .3572527
                                |
                          _cons |   .9588487   .1467441     6.53   0.000      .
> 670962                                                                       
>           1.246735
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,789
                                                F(1, 1787)        =      11.18
                                                Prob > F          =     0.0008
                                                R-squared         =     0.0063
                                                Root MSE          =     .49542

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |    .112448   .0336368     3.34   0.001     .0464765    .1784196
       _cons |   .4266145    .012639    33.75   0.000     .4018257    .4514033
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,331
                                                F(42, 1288)       =      20.76
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2531
                                                Root MSE          =     .43879

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0947727   .0352706     2.69   0.007     .0
> 255787                                                                       
>           .1639668
                         female |  -.0142083    .026048    -0.55   0.586    -.0
> 653095                                                                       
>           .0368928
                                |
                         income |
         Menos o igual a 300 €  |  -.0095435   .0900186    -0.11   0.916    -.1
> 861426                                                                       
>           .1670556
                De 301 a 600 €  |  -.0185977   .0569699    -0.33   0.744    -.1
> 303616                                                                       
>           .0931662
                De 601 a 900 €  |  -.0416781   .0449357    -0.93   0.354    -.1
> 298333                                                                       
>           .0464771
              De 901 a 1.200 €  |  -.0526136   .0426954    -1.23   0.218    -.1
> 363738                                                                       
>           .0311466
            De 1.201 a 1.800 €  |  -.0387881   .0451288    -0.86   0.390    -.1
> 273222                                                                       
>            .049746
            De 1.801 a 2.400 €  |   -.010296   .0538588    -0.19   0.848    -.1
> 159567                                                                       
>           .0953646
            De 2.401 a 3.000 €  |  -.0550464   .0735529    -0.75   0.454    -.1
> 993431                                                                       
>           .0892503
            De 3.001 a 4.500 €  |   .1608926   .1116987     1.44   0.150    -.0
> 582387                                                                       
>            .380024
            De 4.501 a 6.000 €  |  -.4441912   .1808787    -2.46   0.014    -.7
> 990404                                                                       
>           -.089342
                Más de 6.000 €  |   .0118923   .2114558     0.06   0.955    -.4
> 029433                                                                       
>            .426728
                                |
                            age |  -.0001842   .0045452    -0.04   0.968     -.
> 009101                                                                       
>           .0087326
                         age_sq |  -.0000214   .0000473    -0.45   0.651    -.0
> 001142                                                                       
>           .0000715
                                |
                      education |
                      Primaria  |  -.0592685    .105671    -0.56   0.575    -.2
> 665746                                                                       
>           .1480377
           Secundaria 1ª etapa  |  -.1412682   .1068403    -1.32   0.186    -.3
> 508684                                                                       
>            .068332
           Secundaria 2ª etapa  |   -.167422   .1084241    -1.54   0.123    -.3
> 801291                                                                       
>           .0452852
                          F.P.  |  -.0872182   .1076047    -0.81   0.418    -.2
> 983179                                                                       
>           .1238814
                    Superiores  |  -.0928108   .1090725    -0.85   0.395      -
> .30679                                                                       
>           .1211684
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |  -.0158506   .0596427    -0.27   0.790    -.1
> 328581                                                                       
>            .101157
    10.001 a 50.000 habitantes  |  -.1497197   .0579733    -2.58   0.010    -.2
> 634522                                                                       
>          -.0359871
   50.001 a 100.000 habitantes  |  -.1947243   .0642316    -3.03   0.002    -.3
> 207344                                                                       
>          -.0687141
  100.001 a 400.000 habitantes  |  -.2289678   .0598488    -3.83   0.000    -.3
> 463796                                                                       
>           -.111556
400.001 a 1.000.000 habitantes  |  -.4016342   .0675508    -5.95   0.000    -.5
> 341558                                                                       
>          -.2691126
   Más de 1.000.000 habitantes  |  -.2555092   .0634661    -4.03   0.000    -.3
> 800175                                                                       
>          -.1310009
                                |
                           CCAA |
                        Aragón  |  -.0243669   .0691085    -0.35   0.724    -.1
> 599444                                                                       
>           .1112107
      Asturias (Principado de)  |  -.2303058   .0722927    -3.19   0.001    -.3
> 721303                                                                       
>          -.0884814
               Balears (Illes)  |  -.1828629   .0777699    -2.35   0.019    -.3
> 354326                                                                       
>          -.0302933
                      Canarias  |   .3627683   .0538959     6.73   0.000      .
> 257035                                                                       
>           .4685016
                     Cantabria  |  -.0647123   .0688672    -0.94   0.348    -.1
> 998165                                                                       
>           .0703919
            Castilla-La Mancha  |   .0021202   .0709962     0.03   0.976    -.1
> 371608                                                                       
>           .1414012
               Castilla y León  |    .039644   .0710084     0.56   0.577    -.0
> 996609                                                                       
>           .1789489
                      Cataluña  |  -.4435552    .048089    -9.22   0.000    -.5
> 378966                                                                       
>          -.3492138
          Comunitat Valenciana  |  -.0800557   .0543884    -1.47   0.141    -.1
> 867552                                                                       
>           .0266439
                   Extremadura  |   .1467215   .0610966     2.40   0.016     .0
> 268617                                                                       
>           .2665812
                       Galicia  |    -.03288   .0720777    -0.46   0.648    -.1
> 742825                                                                       
>           .1085226
         Madrid (Comunidad de)  |  -.4017347   .0472548    -8.50   0.000    -.4
> 944394                                                                       
>          -.3090299
            Murcia (Región de)  |   .1326561   .0664821     2.00   0.046     .0
> 022309                                                                       
>           .2630812
  Navarra (Comunidad Foral de)  |  -.2089728    .091488    -2.28   0.023    -.3
> 884546                                                                       
>           -.029491
                    País Vasco  |  -.1240435   .0898583    -1.38   0.168    -.3
> 003281                                                                       
>           .0522412
    Ceuta (Ciudad Autónoma de)  |   .2569111   .0869376     2.96   0.003     .0
> 863563                                                                       
>           .4274659
  Melilla (Ciudad Autónoma de)  |   .1285734   .1150372     1.12   0.264    -.0
> 971073                                                                       
>           .3542542
                                |
                          _cons |   .9390179    .146099     6.43   0.000     .6
> 523998                                                                       
>           1.225636
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,787
                                                F(1, 1785)        =      11.27
                                                Prob > F          =     0.0008
                                                R-squared         =     0.0064
                                                Root MSE          =     .49472

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1160391   .0345653     3.36   0.001     .0482464    .1838318
       _cons |   .4214609   .0125615    33.55   0.000      .396824    .4460978
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,330
                                                F(42, 1287)       =      19.43
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2438
                                                Root MSE          =     .44124

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0926252    .035684     2.60   0.010     .0
> 226201                                                                       
>           .1626303
                         female |  -.0154905   .0262436    -0.59   0.555    -.0
> 669755                                                                       
>           .0359945
                                |
                         income |
         Menos o igual a 300 €  |    .005449   .0904164     0.06   0.952    -.1
> 719307                                                                       
>           .1828287
                De 301 a 600 €  |   .0059749    .057221     0.10   0.917    -.1
> 062818                                                                       
>           .1182317
                De 601 a 900 €  |  -.0263418   .0449747    -0.59   0.558    -.1
> 145736                                                                       
>             .06189
              De 901 a 1.200 €  |  -.0348462   .0430486    -0.81   0.418    -.1
> 192993                                                                       
>           .0496069
            De 1.201 a 1.800 €  |  -.0099547   .0455583    -0.22   0.827    -.0
> 993313                                                                       
>            .079422
            De 1.801 a 2.400 €  |   .0108558   .0542799     0.20   0.842     -.
> 095631                                                                       
>           .1173425
            De 2.401 a 3.000 €  |  -.0232927   .0732933    -0.32   0.751    -.1
> 670801                                                                       
>           .1204946
            De 3.001 a 4.500 €  |   .1586387   .1099448     1.44   0.149    -.0
> 570521                                                                       
>           .3743294
            De 4.501 a 6.000 €  |  -.4173949   .1796906    -2.32   0.020    -.7
> 699136                                                                       
>          -.0648762
                Más de 6.000 €  |   .0305631   .2099149     0.15   0.884    -.3
> 812497                                                                       
>            .442376
                                |
                            age |   -.001441   .0045813    -0.31   0.753    -.0
> 104287                                                                       
>           .0075467
                         age_sq |  -6.22e-06   .0000477    -0.13   0.896    -.0
> 000998                                                                       
>           .0000874
                                |
                      education |
                      Primaria  |  -.0544962   .1049285    -0.52   0.604    -.2
> 603459                                                                       
>           .1513534
           Secundaria 1ª etapa  |  -.1284789   .1061659    -1.21   0.226    -.3
> 367562                                                                       
>           .0797984
           Secundaria 2ª etapa  |  -.1588533   .1078138    -1.47   0.141    -.3
> 703633                                                                       
>           .0526567
                          F.P.  |  -.0781675   .1069091    -0.73   0.465    -.2
> 879027                                                                       
>           .1315677
                    Superiores  |   -.094189   .1085721    -0.87   0.386    -.3
> 071867                                                                       
>           .1188086
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0036412   .0596605     0.06   0.951    -.1
> 134013                                                                       
>           .1206837
    10.001 a 50.000 habitantes  |  -.1289942   .0580016    -2.22   0.026    -.2
> 427822                                                                       
>          -.0152062
   50.001 a 100.000 habitantes  |  -.1777482   .0643379    -2.76   0.006    -.3
> 039668                                                                       
>          -.0515296
  100.001 a 400.000 habitantes  |  -.2213782   .0597517    -3.70   0.000    -.3
> 385996                                                                       
>          -.1041568
400.001 a 1.000.000 habitantes  |  -.3857394   .0679661    -5.68   0.000    -.5
> 190759                                                                       
>          -.2524029
   Más de 1.000.000 habitantes  |  -.2437062   .0636807    -3.83   0.000    -.3
> 686356                                                                       
>          -.1187768
                                |
                           CCAA |
                        Aragón  |  -.0251569   .0689253    -0.36   0.715    -.1
> 603751                                                                       
>           .1100613
      Asturias (Principado de)  |  -.2294766   .0727924    -3.15   0.002    -.3
> 722814                                                                       
>          -.0866719
               Balears (Illes)  |  -.1881114    .077782    -2.42   0.016    -.3
> 407047                                                                       
>           -.035518
                      Canarias  |   .3647258   .0540684     6.75   0.000     .2
> 586541                                                                       
>           .4707976
                     Cantabria  |  -.0655266   .0684782    -0.96   0.339    -.1
> 998676                                                                       
>           .0688145
            Castilla-La Mancha  |    .000997   .0710452     0.01   0.989    -.1
> 383801                                                                       
>           .1403741
               Castilla y León  |   .0413721   .0712044     0.58   0.561    -.0
> 983173                                                                       
>           .1810616
                      Cataluña  |  -.4455302   .0482088    -9.24   0.000    -.5
> 401067                                                                       
>          -.3509536
          Comunitat Valenciana  |  -.0838484   .0545134    -1.54   0.124    -.1
> 907934                                                                       
>           .0230965
                   Extremadura  |   .1498752    .061106     2.45   0.014     .0
> 299968                                                                       
>           .2697535
                       Galicia  |  -.0341715   .0721492    -0.47   0.636    -.1
> 757144                                                                       
>           .1073714
         Madrid (Comunidad de)  |  -.4004781   .0473101    -8.46   0.000    -.4
> 932915                                                                       
>          -.3076646
            Murcia (Región de)  |    .131575   .0664071     1.98   0.048      .
> 001297                                                                       
>            .261853
  Navarra (Comunidad Foral de)  |  -.2096027   .0908654    -2.31   0.021    -.3
> 878633                                                                       
>          -.0313422
                    País Vasco  |  -.1234027   .0890483    -1.39   0.166    -.2
> 980984                                                                       
>           .0512931
                    Rioja (La)  |  -.0742415   .1057225    -0.70   0.483    -.2
> 816488                                                                       
>           .1331658
  Melilla (Ciudad Autónoma de)  |   .1296378   .1158219     1.12   0.263    -.0
> 975825                                                                       
>           .3568582
                                |
                          _cons |   .9234759   .1464358     6.31   0.000     .6
> 361969                                                                       
>           1.210755
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,812
                                                F(1, 1810)        =      10.11
                                                Prob > F          =     0.0015
                                                R-squared         =     0.0056
                                                Root MSE          =     .49461

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1080256   .0339719     3.18   0.001     .0413974    .1746538
       _cons |   .4199744   .0124949    33.61   0.000     .3954684    .4444804
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,339
                                                F(42, 1296)       =      20.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.2483
                                                Root MSE          =     .44006

-------------------------------------------------------------------------------
------------------
                                |               Robust
                     cabine_use | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                       pp_dummy |   .0944646   .0352508     2.68   0.007     .0
> 253096                                                                       
>           .1636195
                         female |  -.0085218   .0260776    -0.33   0.744    -.0
> 596808                                                                       
>           .0426372
                                |
                         income |
         Menos o igual a 300 €  |  -.0061208   .0925178    -0.07   0.947    -.1
> 876219                                                                       
>           .1753803
                De 301 a 600 €  |    .001845   .0568144     0.03   0.974    -.1
> 096133                                                                       
>           .1133033
                De 601 a 900 €  |  -.0256509   .0448623    -0.57   0.568    -.1
> 136616                                                                       
>           .0623598
              De 901 a 1.200 €  |  -.0320053   .0428037    -0.75   0.455    -.1
> 159775                                                                       
>           .0519669
            De 1.201 a 1.800 €  |  -.0136604   .0449734    -0.30   0.761     -.
> 101889                                                                       
>           .0745682
            De 1.801 a 2.400 €  |   .0116773   .0538427     0.22   0.828    -.0
> 939512                                                                       
>           .1173058
            De 2.401 a 3.000 €  |   -.019639   .0731362    -0.27   0.788    -.1
> 631172                                                                       
>           .1238393
            De 3.001 a 4.500 €  |   .1614857   .1099356     1.47   0.142    -.0
> 541855                                                                       
>            .377157
            De 4.501 a 6.000 €  |  -.4149853   .1762946    -2.35   0.019    -.7
> 608394                                                                       
>          -.0691312
                Más de 6.000 €  |   .0347362   .2104076     0.17   0.869    -.3
> 780405                                                                       
>           .4475129
                                |
                            age |  -.0007609   .0045473    -0.17   0.867    -.0
> 096817                                                                       
>           .0081599
                         age_sq |   -.000015   .0000473    -0.32   0.751    -.0
> 001078                                                                       
>           .0000778
                                |
                      education |
                      Primaria  |  -.0530253   .1050443    -0.50   0.614    -.2
> 591007                                                                       
>           .1530502
           Secundaria 1ª etapa  |  -.1320083     .10604    -1.24   0.213    -.3
> 400371                                                                       
>           .0760206
           Secundaria 2ª etapa  |  -.1642774   .1076561    -1.53   0.127    -.3
> 754767                                                                       
>           .0469219
                          F.P.  |  -.0854382    .106881    -0.80   0.424    -.2
> 951168                                                                       
>           .1242405
                    Superiores  |   -.104385   .1083642    -0.96   0.336    -.3
> 169735                                                                       
>           .1082035
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0045119   .0596175     0.08   0.940    -.1
> 124455                                                                       
>           .1214692
    10.001 a 50.000 habitantes  |  -.1276892   .0580009    -2.20   0.028    -.2
> 414752                                                                       
>          -.0139032
   50.001 a 100.000 habitantes  |  -.1759072   .0643246    -2.73   0.006    -.3
> 020989                                                                       
>          -.0497154
  100.001 a 400.000 habitantes  |  -.2196068   .0597512    -3.68   0.000    -.3
> 368265                                                                       
>          -.1023871
400.001 a 1.000.000 habitantes  |  -.3831659   .0679115    -5.64   0.000    -.5
> 163943                                                                       
>          -.2499374
   Más de 1.000.000 habitantes  |  -.2417345   .0636864    -3.80   0.000    -.3
> 666742                                                                       
>          -.1167949
                                |
                           CCAA |
                        Aragón  |  -.0240938   .0689419    -0.35   0.727    -.1
> 593438                                                                       
>           .1111563
      Asturias (Principado de)  |  -.2288289   .0726663    -3.15   0.002    -.3
> 713854                                                                       
>          -.0862724
               Balears (Illes)  |  -.1879749    .077808    -2.42   0.016    -.3
> 406184                                                                       
>          -.0353314
                      Canarias  |    .363629   .0539247     6.74   0.000     .2
> 578396                                                                       
>           .4694183
                     Cantabria  |  -.0635115   .0684994    -0.93   0.354    -.1
> 978934                                                                       
>           .0708704
            Castilla-La Mancha  |   .0022629   .0710423     0.03   0.975    -.1
> 371076                                                                       
>           .1416333
               Castilla y León  |   .0425802   .0712607     0.60   0.550    -.0
> 972188                                                                       
>           .1823791
                      Cataluña  |  -.4440726   .0482291    -9.21   0.000    -.5
> 386883                                                                       
>          -.3494568
          Comunitat Valenciana  |  -.0826274   .0544514    -1.52   0.129    -.1
> 894499                                                                       
>           .0241952
                   Extremadura  |   .1510295   .0611189     2.47   0.014     .0
> 311268                                                                       
>           .2709322
                       Galicia  |  -.0334204   .0721459    -0.46   0.643    -.1
> 749559                                                                       
>           .1081152
         Madrid (Comunidad de)  |  -.3990542   .0472944    -8.44   0.000    -.4
> 918363                                                                       
>          -.3062722
            Murcia (Región de)  |   .1322721   .0663211     1.99   0.046     .0
> 021635                                                                       
>           .2623806
  Navarra (Comunidad Foral de)  |  -.2060898   .0910235    -2.26   0.024    -.3
> 846594                                                                       
>          -.0275203
                    País Vasco  |  -.1203588   .0888437    -1.35   0.176    -.2
> 946521                                                                       
>           .0539345
                    Rioja (La)  |  -.0734897   .1058948    -0.69   0.488    -.2
> 812337                                                                       
>           .1342543
    Ceuta (Ciudad Autónoma de)  |   .2548815   .0875437     2.91   0.004     .0
> 831386                                                                       
>           .4266244
                                |
                          _cons |   .9132764   .1460377     6.25   0.000     .6
> 267803                                                                       
>           1.199773
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk.dta saved

Linear regression                               Number of obs     =      1,830
                                                F(1, 1828)        =      10.68
                                                Prob > F          =     0.0011
                                                R-squared         =     0.0059
                                                Root MSE          =     .49525

------------------------------------------------------------------------------
             |               Robust
  cabine_use | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
    pp_dummy |   .1104925   .0338103     3.27   0.001     .0441816    .1768034
       _cons |   .4252218   .0124521    34.15   0.000        .4008    .4496436
------------------------------------------------------------------------------
file 01_data/survey_ccaa_jk.dta saved

. 
end of do-file

. do "/Users/vicentevalentim/Dropbox/JOP third submission/JOP replication/02_co
> de/figured10_1.do"

. * Clean up
. clear all

. 
. /* Set working directory: please set your own
> cd "~/Dropbox/JOP third submission/JOP replication/"
> */
. 
. * Open dataset
. 
. use 01_data/cis_data.dta, clear

. 
. * Generate interaction
. gen cabine_use_pp_dummy = cabine_use * pp_dummy
(2,957 missing values generated)

. 
. * A fake model to start the dataset
. regr cabine_use CCAA

      Source |       SS           df       MS      Number of obs   =     1,848
-------------+----------------------------------   F(1, 1846)      =      4.17
       Model |  1.02665746         1  1.02665746   Prob > F        =    0.0414
    Residual |  455.007433     1,846    .2464829   R-squared       =    0.0023
-------------+----------------------------------   Adj R-squared   =    0.0017
       Total |  456.034091     1,847  .246905301   Root MSE        =    .49647

------------------------------------------------------------------------------
  cabine_use | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
        CCAA |  -.0046489   .0022779    -2.04   0.041    -.0091163   -.0001814
       _cons |   .4829034   .0226314    21.34   0.000     .4385175    .5272892
------------------------------------------------------------------------------

. regsave CCAA using 01_data/survey_ccaa_jk_2.dta, ci level(95) replace addlabe
> l ///
> (Removed, fake, Model, fake, Controls, fake)
file 01_data/survey_ccaa_jk_2.dta saved

. 
. forvalues x = 1/19{
  2.         regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy female 
> i.income age age_sq i.education i.TAMUNI i.CCAA if CCAA != `x', r
  3.         regsave cabine_use_pp_dummy using 01_data/survey_ccaa_jk_2.dta, ci
>  level(95) append addlabel ///
> (Removed, `x', Model, uncomfortable, Controls, With controls)
  4. 
.         regr uncomfortable cabine_use pp_dummy cabine_use_pp_dummy if CCAA !=
>  `x', r
  5.         regsave cabine_use_pp_dummy using 01_data/survey_ccaa_jk_2.dta, ci
>  level(95) append addlabel ///
> (Removed, `x', Model, uncomfortable, Controls, Without controls)
  6. 
. }

Linear regression                               Number of obs     =      1,125
                                                F(44, 1080)       =       2.02
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0883
                                                Root MSE          =     .27608

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0070044   .0180295    -0.39   0.698    -.0
> 423812                                                                       
>           .0283725
                       pp_dummy |  -.0324816   .0353849    -0.92   0.359    -.1
> 019125                                                                       
>           .0369493
            cabine_use_pp_dummy |   .1307895   .0550187     2.38   0.018     .0
> 228338                                                                       
>           .2387452
                         female |   .0301597   .0171375     1.76   0.079    -.0
> 034669                                                                       
>           .0637863
                                |
                         income |
         Menos o igual a 300 €  |   .0647427   .0746581     0.87   0.386    -.0
> 817487                                                                       
>            .211234
                De 301 a 600 €  |   .1042461    .045653     2.28   0.023     .0
> 146675                                                                       
>           .1938247
                De 601 a 900 €  |   .0254071   .0342889     0.74   0.459    -.0
> 418733                                                                       
>           .0926876
              De 901 a 1.200 €  |   .0240149   .0303814     0.79   0.429    -.0
> 355983                                                                       
>           .0836281
            De 1.201 a 1.800 €  |   .0127271   .0299307     0.43   0.671    -.0
> 460018                                                                       
>            .071456
            De 1.801 a 2.400 €  |   -.030205   .0323197    -0.93   0.350    -.0
> 936216                                                                       
>           .0332116
            De 2.401 a 3.000 €  |  -.0139752   .0475614    -0.29   0.769    -.1
> 072985                                                                       
>            .079348
            De 3.001 a 4.500 €  |   .0922343   .0775222     1.19   0.234    -.0
> 598768                                                                       
>           .2443455
            De 4.501 a 6.000 €  |  -.0669221   .0531927    -1.26   0.209    -.1
> 712949                                                                       
>           .0374507
                Más de 6.000 €  |  -.0640743   .0500951    -1.28   0.201    -.1
> 623691                                                                       
>           .0342206
                                |
                            age |    .000143   .0033295     0.04   0.966      -
> .00639                                                                       
>            .006676
                         age_sq |  -7.84e-07   .0000353    -0.02   0.982      -
> .00007                                                                       
>           .0000685
                                |
                      education |
                      Primaria  |  -.1238642   .1257708    -0.98   0.325    -.3
> 706471                                                                       
>           .1229186
           Secundaria 1ª etapa  |  -.1314701   .1270375    -1.03   0.301    -.3
> 807383                                                                       
>           .1177981
           Secundaria 2ª etapa  |  -.1549182   .1281201    -1.21   0.227    -.4
> 063107                                                                       
>           .0964742
                          F.P.  |  -.1482678   .1278291    -1.16   0.246    -.3
> 990894                                                                       
>           .1025538
                    Superiores  |  -.1387329   .1283005    -1.08   0.280    -.3
> 904794                                                                       
>           .1130137
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .032195   .0382183     0.84   0.400    -.0
> 427956                                                                       
>           .1071856
    10.001 a 50.000 habitantes  |   .0198787   .0330163     0.60   0.547    -.0
> 449046                                                                       
>            .084662
   50.001 a 100.000 habitantes  |   .0178312    .040557     0.44   0.660    -.0
> 617483                                                                       
>           .0974106
  100.001 a 400.000 habitantes  |  -.0057275   .0349021    -0.16   0.870     -.
> 074211                                                                       
>            .062756
400.001 a 1.000.000 habitantes  |  -.0096477   .0408557    -0.24   0.813    -.0
> 898132                                                                       
>           .0705179
   Más de 1.000.000 habitantes  |  -.1034206    .043053    -2.40   0.016    -.1
> 878975                                                                       
>          -.0189437
                                |
                           CCAA |
      Asturias (Principado de)  |   .0880525   .0605317     1.45   0.146    -.0
> 307206                                                                       
>           .2068256
               Balears (Illes)  |   .0721245   .0544869     1.32   0.186    -.0
> 347877                                                                       
>           .1790368
                      Canarias  |  -.0370505   .0437457    -0.85   0.397    -.1
> 228868                                                                       
>           .0487858
                     Cantabria  |   .0015287   .0429599     0.04   0.972    -.0
> 827656                                                                       
>            .085823
            Castilla-La Mancha  |   .1556299   .0654654     2.38   0.018     .0
> 271762                                                                       
>           .2840836
               Castilla y León  |   .1165076   .0623052     1.87   0.062    -.0
> 057454                                                                       
>           .2387607
                      Cataluña  |   .0502432   .0428883     1.17   0.242    -.0
> 339107                                                                       
>            .134397
          Comunitat Valenciana  |   -.024796   .0370273    -0.67   0.503    -.0
> 974496                                                                       
>           .0478575
                   Extremadura  |   .0061832   .0502593     0.12   0.902    -.0
> 924336                                                                       
>           .1048001
                       Galicia  |  -.0556452   .0385098    -1.44   0.149    -.1
> 312076                                                                       
>           .0199173
         Madrid (Comunidad de)  |   .1343281   .0487667     2.75   0.006     .0
> 386399                                                                       
>           .2300162
            Murcia (Región de)  |  -.0447648   .0342438    -1.31   0.191    -.1
> 119567                                                                       
>           .0224271
  Navarra (Comunidad Foral de)  |   .0246209   .0605975     0.41   0.685    -.0
> 942812                                                                       
>            .143523
                    País Vasco  |  -.0214006   .0456081    -0.47   0.639    -.1
> 108911                                                                       
>           .0680898
                    Rioja (La)  |  -.0574793   .0371135    -1.55   0.122     -.
> 130302                                                                       
>           .0153433
    Ceuta (Ciudad Autónoma de)  |   .1190655   .0861323     1.38   0.167    -.0
> 499402                                                                       
>           .2880712
  Melilla (Ciudad Autónoma de)  |  -.0202323   .0712832    -0.28   0.777    -.1
> 601016                                                                       
>            .119637
                                |
                          _cons |   .1504193   .1440194     1.04   0.297    -.1
> 321702                                                                       
>           .4330088
-------------------------------------------------------------------------------
------------------
(note: variable Removed was str4 in the using data, but will be byte now)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,554
                                                F(3, 1550)        =       2.70
                                                Prob > F          =     0.0442
                                                R-squared         =     0.0086
                                                Root MSE          =     .29703

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0114342   .0158752    -0.72   0.471    -.0425733    .0
> 197049
           pp_dummy |  -.0175257   .0288797    -0.61   0.544    -.0741731    .0
> 391216
cabine_use_pp_dummy |   .1303395   .0497855     2.62   0.009     .0326855    .2
> 279935
              _cons |   .0967337   .0104906     9.22   0.000     .0761564    .1
> 173109
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,298
                                                F(44, 1253)       =       2.32
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0775
                                                Root MSE          =      .2821

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0161033   .0181351    -0.89   0.375    -.0
> 516817                                                                       
>           .0194752
                       pp_dummy |  -.0397641   .0296385    -1.34   0.180    -.0
> 979106                                                                       
>           .0183824
            cabine_use_pp_dummy |   .1019231   .0460939     2.21   0.027     .0
> 114935                                                                       
>           .1923527
                         female |   .0250148   .0163932     1.53   0.127    -.0
> 071464                                                                       
>           .0571759
                                |
                         income |
         Menos o igual a 300 €  |  -.0018772   .0600616    -0.03   0.975    -.1
> 197096                                                                       
>           .1159553
                De 301 a 600 €  |   .0862989   .0411849     2.10   0.036       
>  .0055                                                                       
>           .1670978
                De 601 a 900 €  |   .0169732   .0309245     0.55   0.583    -.0
> 436962                                                                       
>           .0776426
              De 901 a 1.200 €  |    .015556    .028605     0.54   0.587     -.
> 040563                                                                       
>           .0716749
            De 1.201 a 1.800 €  |   .0061002   .0281259     0.22   0.828    -.0
> 490787                                                                       
>           .0612792
            De 1.801 a 2.400 €  |   -.038499   .0311276    -1.24   0.216     -.
> 099567                                                                       
>            .022569
            De 2.401 a 3.000 €  |    -.02738   .0428324    -0.64   0.523    -.1
> 114111                                                                       
>            .056651
            De 3.001 a 4.500 €  |   .0666088   .0719178     0.93   0.355    -.0
> 744838                                                                       
>           .2077014
            De 4.501 a 6.000 €  |  -.0807269   .0470685    -1.72   0.087    -.1
> 730688                                                                       
>           .0116149
                Más de 6.000 €  |   -.075983   .0432943    -1.76   0.079    -.1
> 609203                                                                       
>           .0089544
                                |
                            age |  -.0011034   .0032132    -0.34   0.731    -.0
> 074072                                                                       
>           .0052003
                         age_sq |   .0000158   .0000342     0.46   0.643    -.0
> 000512                                                                       
>           .0000828
                                |
                      education |
                      Primaria  |  -.0840881   .0929996    -0.90   0.366    -.2
> 665403                                                                       
>           .0983641
           Secundaria 1ª etapa  |  -.0383772     .09501    -0.40   0.686    -.2
> 247734                                                                       
>           .1480191
           Secundaria 2ª etapa  |  -.0903516   .0954975    -0.95   0.344    -.2
> 777043                                                                       
>           .0970011
                          F.P.  |  -.0792829   .0949966    -0.83   0.404    -.2
> 656528                                                                       
>           .1070871
                    Superiores  |  -.0694564   .0958619    -0.72   0.469     -.
> 257524                                                                       
>           .1186112
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0587715   .0398486     1.47   0.140    -.0
> 194059                                                                       
>           .1369489
    10.001 a 50.000 habitantes  |   .0268647   .0358685     0.75   0.454    -.0
> 435042                                                                       
>           .0972337
   50.001 a 100.000 habitantes  |    .012207   .0407215     0.30   0.764    -.0
> 676829                                                                       
>           .0920969
  100.001 a 400.000 habitantes  |  -.0018723   .0365205    -0.05   0.959    -.0
> 735204                                                                       
>           .0697758
400.001 a 1.000.000 habitantes  |  -.0375148   .0410563    -0.91   0.361    -.1
> 180615                                                                       
>            .043032
   Más de 1.000.000 habitantes  |  -.1000867   .0447435    -2.24   0.025     -.
> 187867                                                                       
>          -.0123063
                                |
                           CCAA |
      Asturias (Principado de)  |   .0550168   .0544203     1.01   0.312    -.0
> 517481                                                                       
>           .1617818
               Balears (Illes)  |   .0530035   .0517142     1.02   0.306    -.0
> 484525                                                                       
>           .1544595
                      Canarias  |  -.0631052   .0343968    -1.83   0.067    -.1
> 305868                                                                       
>           .0043765
                     Cantabria  |  -.0354785   .0370034    -0.96   0.338     -.
> 108074                                                                       
>            .037117
            Castilla-La Mancha  |   .1276526   .0597766     2.14   0.033     .0
> 103793                                                                       
>           .2449259
               Castilla y León  |   .0858358   .0555169     1.55   0.122    -.0
> 230805                                                                       
>           .1947521
                      Cataluña  |   .0087677   .0355047     0.25   0.805    -.0
> 608875                                                                       
>           .0784229
          Comunitat Valenciana  |  -.0543982   .0275722    -1.97   0.049     -.
> 108491                                                                       
>          -.0003053
                   Extremadura  |  -.0194284   .0436533    -0.45   0.656      -
> .10507                                                                       
>           .0662132
                       Galicia  |  -.0945348    .028791    -3.28   0.001    -.1
> 510185                                                                       
>           -.038051
         Madrid (Comunidad de)  |   .0967054    .041719     2.32   0.021     .0
> 148585                                                                       
>           .1785522
            Murcia (Región de)  |  -.0636512   .0249014    -2.56   0.011    -.1
> 125043                                                                       
>           -.014798
  Navarra (Comunidad Foral de)  |  -.0180523   .0562077    -0.32   0.748     -.
> 128324                                                                       
>           .0922193
                    País Vasco  |  -.0625012   .0364225    -1.72   0.086     -.
> 133957                                                                       
>           .0089546
                    Rioja (La)  |  -.0910961   .0263369    -3.46   0.001    -.1
> 427654                                                                       
>          -.0394267
    Ceuta (Ciudad Autónoma de)  |   .0922987   .0815315     1.13   0.258    -.0
> 676546                                                                       
>           .2522521
  Melilla (Ciudad Autónoma de)  |  -.0324519   .0644378    -0.50   0.615    -.1
> 588698                                                                       
>            .093966
                                |
                          _cons |    .145818   .1126715     1.29   0.196    -.0
> 752277                                                                       
>           .3668636
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,772
                                                F(3, 1768)        =       1.97
                                                Prob > F          =     0.1163
                                                R-squared         =     0.0046
                                                Root MSE          =     .30323

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0081906   .0153972    -0.53   0.595    -.0383893     .
> 022008
           pp_dummy |  -.0252583   .0267175    -0.95   0.345    -.0776596     .
> 027143
cabine_use_pp_dummy |   .1016379   .0435281     2.33   0.020     .0162659      
> .18701
              _cons |   .1021814   .0102745     9.95   0.000     .0820299    .1
> 223329
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,306
                                                F(44, 1261)       =       2.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0786
                                                Root MSE          =     .27682

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0159597   .0175906    -0.91   0.364    -.0
> 504698                                                                       
>           .0185504
                       pp_dummy |  -.0505037   .0280717    -1.80   0.072    -.1
> 055761                                                                       
>           .0045688
            cabine_use_pp_dummy |   .1121036   .0445882     2.51   0.012     .0
> 246284                                                                       
>           .1995788
                         female |   .0323562   .0159528     2.03   0.043     .0
> 010593                                                                       
>           .0636532
                                |
                         income |
         Menos o igual a 300 €  |   .0014716    .059474     0.02   0.980    -.1
> 152073                                                                       
>           .1181504
                De 301 a 600 €  |   .0773002   .0404233     1.91   0.056    -.0
> 020042                                                                       
>           .1566046
                De 601 a 900 €  |   .0161262   .0308585     0.52   0.601    -.0
> 444135                                                                       
>            .076666
              De 901 a 1.200 €  |   .0113869   .0282307     0.40   0.687    -.0
> 439973                                                                       
>           .0667712
            De 1.201 a 1.800 €  |   .0158474   .0283569     0.56   0.576    -.0
> 397845                                                                       
>           .0714793
            De 1.801 a 2.400 €  |  -.0361727   .0300058    -1.21   0.228    -.0
> 950394                                                                       
>           .0226941
            De 2.401 a 3.000 €  |  -.0165687   .0434993    -0.38   0.703    -.1
> 019076                                                                       
>           .0687702
            De 3.001 a 4.500 €  |   .0652364   .0673126     0.97   0.333    -.0
> 668205                                                                       
>           .1972933
            De 4.501 a 6.000 €  |  -.0777236   .0476145    -1.63   0.103     -.
> 171136                                                                       
>           .0156888
                Más de 6.000 €  |  -.0695216   .0410792    -1.69   0.091    -.1
> 501128                                                                       
>           .0110695
                                |
                            age |  -.0022042   .0031744    -0.69   0.488    -.0
> 084319                                                                       
>           .0040235
                         age_sq |   .0000265   .0000337     0.79   0.431    -.0
> 000395                                                                       
>           .0000925
                                |
                      education |
                      Primaria  |  -.0999136    .099327    -1.01   0.315    -.2
> 947779                                                                       
>           .0949507
           Secundaria 1ª etapa  |  -.0779207   .1015327    -0.77   0.443    -.2
> 771124                                                                       
>            .121271
           Secundaria 2ª etapa  |   -.112508   .1021022    -1.10   0.271    -.3
> 128168                                                                       
>           .0878009
                          F.P.  |  -.1025681    .101551    -1.01   0.313    -.3
> 017956                                                                       
>           .0966593
                    Superiores  |  -.0952694   .1022034    -0.93   0.351    -.2
> 957768                                                                       
>            .105238
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0566885   .0373124     1.52   0.129    -.0
> 165127                                                                       
>           .1298897
    10.001 a 50.000 habitantes  |   .0179976   .0328136     0.55   0.583    -.0
> 463776                                                                       
>           .0823729
   50.001 a 100.000 habitantes  |  -.0001096    .037977    -0.00   0.998    -.0
> 746147                                                                       
>           .0743954
  100.001 a 400.000 habitantes  |  -.0083084   .0339208    -0.24   0.807    -.0
> 748557                                                                       
>           .0582389
400.001 a 1.000.000 habitantes  |  -.0405397   .0362427    -1.12   0.264    -.1
> 116424                                                                       
>            .030563
   Más de 1.000.000 habitantes  |   -.107718   .0427527    -2.52   0.012    -.1
> 915923                                                                       
>          -.0238437
                                |
                           CCAA |
                        Aragón  |  -.0249033    .035807    -0.70   0.487    -.0
> 951511                                                                       
>           .0453444
               Balears (Illes)  |   .0498676   .0520083     0.96   0.338    -.0
> 521647                                                                       
>           .1518999
                      Canarias  |  -.0616341   .0343201    -1.80   0.073    -.1
> 289649                                                                       
>           .0056967
                     Cantabria  |  -.0376064   .0368725    -1.02   0.308    -.1
> 099445                                                                       
>           .0347317
            Castilla-La Mancha  |   .1276845   .0597676     2.14   0.033     .0
> 104296                                                                       
>           .2449394
               Castilla y León  |   .0806411   .0553858     1.46   0.146    -.0
> 280174                                                                       
>           .1892997
                      Cataluña  |   .0068401   .0351328     0.19   0.846    -.0
> 620852                                                                       
>           .0757654
          Comunitat Valenciana  |  -.0548685    .027489    -2.00   0.046    -.1
> 087977                                                                       
>          -.0009393
                   Extremadura  |   -.019232   .0428498    -0.45   0.654    -.1
> 032968                                                                       
>           .0648328
                       Galicia  |  -.0938755   .0286288    -3.28   0.001    -.1
> 500409                                                                       
>          -.0377101
         Madrid (Comunidad de)  |   .0974641   .0414749     2.35   0.019     .0
> 160967                                                                       
>           .1788315
            Murcia (Región de)  |   -.065157   .0248305    -2.62   0.009    -.1
> 138705                                                                       
>          -.0164434
  Navarra (Comunidad Foral de)  |  -.0205165   .0559564    -0.37   0.714    -.1
> 302944                                                                       
>           .0892614
                    País Vasco  |  -.0643869   .0362126    -1.78   0.076    -.1
> 354304                                                                       
>           .0066567
                    Rioja (La)  |  -.0902945   .0257706    -3.50   0.000    -.1
> 408525                                                                       
>          -.0397365
    Ceuta (Ciudad Autónoma de)  |   .0982742      .0818     1.20   0.230    -.0
> 622048                                                                       
>           .2587532
  Melilla (Ciudad Autónoma de)  |  -.0244978   .0642677    -0.38   0.703    -.1
> 505811                                                                       
>           .1015855
                                |
                          _cons |   .2004722   .1163242     1.72   0.085    -.0
> 277382                                                                       
>           .4286825
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,785
                                                F(3, 1781)        =       1.90
                                                Prob > F          =     0.1273
                                                R-squared         =     0.0042
                                                Root MSE          =     .29783

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |   -.005332   .0150919    -0.35   0.724    -.0349317    .0
> 242677
           pp_dummy |  -.0279118   .0257917    -1.08   0.279    -.0784971    .0
> 226734
cabine_use_pp_dummy |   .0975315   .0423218     2.30   0.021     .0145258    .1
> 805372
              _cons |   .0974771   .0100556     9.69   0.000      .077755    .1
> 171991
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,307
                                                F(44, 1262)       =       2.25
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0773
                                                Root MSE          =     .27801

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0138119   .0175902    -0.79   0.432    -.0
> 483211                                                                       
>           .0206974
                       pp_dummy |  -.0493527   .0280981    -1.76   0.079    -.1
> 044767                                                                       
>           .0057714
            cabine_use_pp_dummy |    .114636   .0452722     2.53   0.011     .0
> 258189                                                                       
>            .203453
                         female |   .0254688   .0160072     1.59   0.112     -.
> 005935                                                                       
>           .0568725
                                |
                         income |
         Menos o igual a 300 €  |   .0276587   .0660325     0.42   0.675    -.1
> 018869                                                                       
>           .1572043
                De 301 a 600 €  |   .0748218    .040847     1.83   0.067    -.0
> 053138                                                                       
>           .1549573
                De 601 a 900 €  |   .0126282   .0308115     0.41   0.682    -.0
> 478192                                                                       
>           .0730756
              De 901 a 1.200 €  |  -.0020209   .0278458    -0.07   0.942    -.0
> 566501                                                                       
>           .0526083
            De 1.201 a 1.800 €  |   .0092856   .0281975     0.33   0.742    -.0
> 460336                                                                       
>           .0646048
            De 1.801 a 2.400 €  |  -.0364586    .030721    -1.19   0.236    -.0
> 967285                                                                       
>           .0238113
            De 2.401 a 3.000 €  |  -.0215168    .045042    -0.48   0.633    -.1
> 098823                                                                       
>           .0668488
            De 3.001 a 4.500 €  |   .0644699   .0698584     0.92   0.356    -.0
> 725814                                                                       
>           .2015212
            De 4.501 a 6.000 €  |  -.0742989   .0458789    -1.62   0.106    -.1
> 643062                                                                       
>           .0157084
                Más de 6.000 €  |   -.075866   .0412897    -1.84   0.066    -.1
> 568701                                                                       
>           .0051381
                                |
                            age |  -.0007101   .0032065    -0.22   0.825    -.0
> 070007                                                                       
>           .0055805
                         age_sq |   .0000113   .0000342     0.33   0.740    -.0
> 000557                                                                       
>           .0000784
                                |
                      education |
                      Primaria  |  -.0935311   .0957116    -0.98   0.329    -.2
> 813024                                                                       
>           .0942403
           Secundaria 1ª etapa  |  -.0634638   .0977612    -0.65   0.516    -.2
> 552561                                                                       
>           .1283285
           Secundaria 2ª etapa  |  -.1061041   .0982192    -1.08   0.280     -.
> 298795                                                                       
>           .0865867
                          F.P.  |  -.1028246   .0974556    -1.06   0.292    -.2
> 940175                                                                       
>           .0883683
                    Superiores  |  -.0961762   .0980906    -0.98   0.327    -.2
> 886149                                                                       
>           .0962624
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0579432   .0375411     1.54   0.123    -.0
> 157067                                                                       
>           .1315931
    10.001 a 50.000 habitantes  |   .0125932   .0330595     0.38   0.703    -.0
> 522645                                                                       
>           .0774509
   50.001 a 100.000 habitantes  |   .0045828   .0379727     0.12   0.904    -.0
> 699138                                                                       
>           .0790794
  100.001 a 400.000 habitantes  |  -.0084996    .034058    -0.25   0.803    -.0
> 753162                                                                       
>            .058317
400.001 a 1.000.000 habitantes  |  -.0261523   .0359044    -0.73   0.467    -.0
> 965912                                                                       
>           .0442866
   Más de 1.000.000 habitantes  |  -.1056014   .0429071    -2.46   0.014    -.1
> 897784                                                                       
>          -.0214243
                                |
                           CCAA |
                        Aragón  |   -.026199   .0353344    -0.74   0.459    -.0
> 955197                                                                       
>           .0431217
      Asturias (Principado de)  |    .058111   .0545864     1.06   0.287    -.0
> 489792                                                                       
>           .1652011
                      Canarias  |  -.0573983    .034654    -1.66   0.098     -.
> 125384                                                                       
>           .0105874
                     Cantabria  |  -.0332824   .0367555    -0.91   0.365     -.
> 105391                                                                       
>           .0388263
            Castilla-La Mancha  |   .1296795   .0600428     2.16   0.031     .0
> 118847                                                                       
>           .2474742
               Castilla y León  |   .0851978   .0553901     1.54   0.124     -.
> 023469                                                                       
>           .1938646
                      Cataluña  |   .0125357   .0352531     0.36   0.722    -.0
> 566255                                                                       
>           .0816969
          Comunitat Valenciana  |   -.053903   .0275926    -1.95   0.051    -.1
> 080354                                                                       
>           .0002294
                   Extremadura  |   -.018517   .0431522    -0.43   0.668    -.1
> 031749                                                                       
>           .0661409
                       Galicia  |  -.0885831   .0288406    -3.07   0.002    -.1
> 451639                                                                       
>          -.0320022
         Madrid (Comunidad de)  |   .1024028   .0415386     2.47   0.014     .0
> 209105                                                                       
>           .1838952
            Murcia (Región de)  |  -.0652308   .0245874    -2.65   0.008    -.1
> 134674                                                                       
>          -.0169942
  Navarra (Comunidad Foral de)  |  -.0137439   .0556947    -0.25   0.805    -.1
> 230084                                                                       
>           .0955205
                    País Vasco  |  -.0563033   .0360676    -1.56   0.119    -.1
> 270623                                                                       
>           .0144557
                    Rioja (La)  |  -.0873802   .0260434    -3.36   0.001    -.1
> 384734                                                                       
>           -.036287
    Ceuta (Ciudad Autónoma de)  |   .0954327    .081369     1.17   0.241    -.0
> 642008                                                                       
>           .2550661
  Melilla (Ciudad Autónoma de)  |  -.0270279   .0639712    -0.42   0.673    -.1
> 525296                                                                       
>           .0984738
                                |
                          _cons |   .1659366   .1141106     1.45   0.146    -.0
> 579307                                                                       
>           .3898039
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,768
                                                F(3, 1764)        =       2.79
                                                Prob > F          =     0.0391
                                                R-squared         =     0.0063
                                                Root MSE          =     .30104

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0085206   .0152531    -0.56   0.576    -.0384366    .0
> 213954
           pp_dummy |  -.0364663   .0256208    -1.42   0.155    -.0867167    .0
> 137841
cabine_use_pp_dummy |   .1234049   .0434159     2.84   0.005     .0382528     .
> 208557
              _cons |   .1006865   .0101901     9.88   0.000     .0807006    .1
> 206724
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,316
                                                F(44, 1271)       =       2.36
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0769
                                                Root MSE          =     .28249

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0168943   .0176365    -0.96   0.338    -.0
> 514942                                                                       
>           .0177057
                       pp_dummy |  -.0384221   .0296884    -1.29   0.196    -.0
> 966658                                                                       
>           .0198215
            cabine_use_pp_dummy |   .1087815   .0465875     2.33   0.020     .0
> 173846                                                                       
>           .2001784
                         female |   .0277702   .0162347     1.71   0.087    -.0
> 040795                                                                       
>           .0596198
                                |
                         income |
         Menos o igual a 300 €  |   .0283034   .0674252     0.42   0.675    -.1
> 039734                                                                       
>           .1605803
                De 301 a 600 €  |   .0845011    .041919     2.02   0.044      .
> 002263                                                                       
>           .1667391
                De 601 a 900 €  |   .0096925   .0313492     0.31   0.757    -.0
> 518093                                                                       
>           .0711943
              De 901 a 1.200 €  |   .0061774   .0286111     0.22   0.829    -.0
> 499527                                                                       
>           .0623076
            De 1.201 a 1.800 €  |   .0056781    .028264     0.20   0.841    -.0
> 497711                                                                       
>           .0611273
            De 1.801 a 2.400 €  |  -.0388371   .0308882    -1.26   0.209    -.0
> 994345                                                                       
>           .0217604
            De 2.401 a 3.000 €  |  -.0270166   .0427892    -0.63   0.528    -.1
> 109619                                                                       
>           .0569287
            De 3.001 a 4.500 €  |   .0624659   .0674366     0.93   0.354    -.0
> 698333                                                                       
>           .1947652
            De 4.501 a 6.000 €  |  -.0769468   .0467558    -1.65   0.100    -.1
> 686739                                                                       
>           .0147804
                Más de 6.000 €  |  -.0730111   .0419873    -1.74   0.082    -.1
> 553831                                                                       
>           .0093609
                                |
                            age |  -.0010229   .0031655    -0.32   0.747    -.0
> 072332                                                                       
>           .0051873
                         age_sq |   .0000152   .0000335     0.46   0.649    -.0
> 000505                                                                       
>           .0000809
                                |
                      education |
                      Primaria  |  -.0800159   .0925905    -0.86   0.388     -.
> 261663                                                                       
>           .1016311
           Secundaria 1ª etapa  |  -.0414534   .0948368    -0.44   0.662    -.2
> 275073                                                                       
>           .1446004
           Secundaria 2ª etapa  |  -.0899134   .0952394    -0.94   0.345    -.2
> 767571                                                                       
>           .0969304
                          F.P.  |  -.0787877   .0946625    -0.83   0.405    -.2
> 644997                                                                       
>           .1069243
                    Superiores  |   -.077095   .0952909    -0.81   0.419    -.2
> 640398                                                                       
>           .1098498
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0553205   .0370904     1.49   0.136    -.0
> 174448                                                                       
>           .1280857
    10.001 a 50.000 habitantes  |   .0202797   .0327679     0.62   0.536    -.0
> 440054                                                                       
>           .0845649
   50.001 a 100.000 habitantes  |  -.0007193   .0375677    -0.02   0.985    -.0
> 744208                                                                       
>           .0729821
  100.001 a 400.000 habitantes  |  -.0057752   .0340921    -0.17   0.866    -.0
> 726581                                                                       
>           .0611077
400.001 a 1.000.000 habitantes  |   -.039111   .0361032    -1.08   0.279    -.1
> 099393                                                                       
>           .0317174
   Más de 1.000.000 habitantes  |  -.1042663   .0427443    -2.44   0.015    -.1
> 881234                                                                       
>          -.0204091
                                |
                           CCAA |
                        Aragón  |  -.0213135     .03568    -0.60   0.550    -.0
> 913117                                                                       
>           .0486848
      Asturias (Principado de)  |   .0563454   .0541806     1.04   0.299    -.0
> 499478                                                                       
>           .1626386
               Balears (Illes)  |   .0535157   .0517736     1.03   0.301    -.0
> 480554                                                                       
>           .1550869
                     Cantabria  |  -.0355115   .0364563    -0.97   0.330    -.1
> 070327                                                                       
>           .0360097
            Castilla-La Mancha  |   .1276814   .0598443     2.13   0.033      .
> 010277                                                                       
>           .2450859
               Castilla y León  |   .0846251   .0552667     1.53   0.126    -.0
> 237989                                                                       
>           .1930491
                      Cataluña  |   .0084892    .035212     0.24   0.810    -.0
> 605908                                                                       
>           .0775693
          Comunitat Valenciana  |  -.0547935   .0276529    -1.98   0.048    -.1
> 090439                                                                       
>           -.000543
                   Extremadura  |  -.0202974   .0433707    -0.47   0.640    -.1
> 053834                                                                       
>           .0647885
                       Galicia  |   -.093163   .0285469    -3.26   0.001    -.1
> 491673                                                                       
>          -.0371587
         Madrid (Comunidad de)  |   .0983595   .0415352     2.37   0.018     .0
> 168744                                                                       
>           .1798446
            Murcia (Región de)  |  -.0643834   .0247102    -2.61   0.009    -.1
> 128606                                                                       
>          -.0159061
  Navarra (Comunidad Foral de)  |  -.0160146   .0558578    -0.29   0.774    -.1
> 255983                                                                       
>            .093569
                    País Vasco  |  -.0604725     .03631    -1.67   0.096    -.1
> 317067                                                                       
>           .0107617
                    Rioja (La)  |  -.0923563   .0259751    -3.56   0.000     -.
> 143315                                                                       
>          -.0413977
    Ceuta (Ciudad Autónoma de)  |   .0986568   .0810671     1.22   0.224    -.0
> 603832                                                                       
>           .2576968
  Melilla (Ciudad Autónoma de)  |  -.0256489   .0641994    -0.40   0.690    -.1
> 515974                                                                       
>           .1002995
                                |
                          _cons |   .1517356   .1114362     1.36   0.174    -.0
> 668835                                                                       
>           .3703547
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,796
                                                F(3, 1792)        =       2.23
                                                Prob > F          =     0.0833
                                                R-squared         =     0.0052
                                                Root MSE          =     .30424

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0080476   .0153859    -0.52   0.601    -.0382238    .0
> 221285
           pp_dummy |  -.0262646   .0264591    -0.99   0.321    -.0781586    .0
> 256293
cabine_use_pp_dummy |    .108247   .0436589     2.48   0.013     .0226192    .1
> 938748
              _cons |   .1025358   .0100839    10.17   0.000     .0827585    .1
> 223132
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,288
                                                F(44, 1243)       =       2.30
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0757
                                                Root MSE          =     .28232

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0152785   .0181162    -0.84   0.399    -.0
> 508202                                                                       
>           .0202632
                       pp_dummy |  -.0365385   .0317925    -1.15   0.251    -.0
> 989113                                                                       
>           .0258343
            cabine_use_pp_dummy |   .1150617    .049131     2.34   0.019     .0
> 186728                                                                       
>           .2114506
                         female |    .032325   .0163267     1.98   0.048     .0
> 002941                                                                       
>           .0643559
                                |
                         income |
         Menos o igual a 300 €  |   .0230593   .0639815     0.36   0.719    -.1
> 024643                                                                       
>            .148583
                De 301 a 600 €  |    .062534   .0400053     1.56   0.118    -.0
> 159513                                                                       
>           .1410193
                De 601 a 900 €  |   .0063759   .0313018     0.20   0.839    -.0
> 550343                                                                       
>           .0677861
              De 901 a 1.200 €  |   .0140844   .0296057     0.48   0.634    -.0
> 439982                                                                       
>            .072167
            De 1.201 a 1.800 €  |   .0070486    .029109     0.24   0.809    -.0
> 500597                                                                       
>           .0641569
            De 1.801 a 2.400 €  |  -.0379105   .0316074    -1.20   0.231    -.0
> 999202                                                                       
>           .0240993
            De 2.401 a 3.000 €  |   -.025539   .0450485    -0.57   0.571    -.1
> 139184                                                                       
>           .0628405
            De 3.001 a 4.500 €  |   .0658039   .0727622     0.90   0.366    -.0
> 769463                                                                       
>           .2085542
            De 4.501 a 6.000 €  |  -.0774217   .0484281    -1.60   0.110    -.1
> 724315                                                                       
>           .0175881
                Más de 6.000 €  |  -.0806814   .0479146    -1.68   0.092     -.
> 174684                                                                       
>           .0133211
                                |
                            age |  -.0017997   .0032776    -0.55   0.583      -
> .00823                                                                       
>           .0046306
                         age_sq |    .000023   .0000348     0.66   0.509    -.0
> 000453                                                                       
>           .0000913
                                |
                      education |
                      Primaria  |  -.0751436   .0931887    -0.81   0.420    -.2
> 579682                                                                       
>            .107681
           Secundaria 1ª etapa  |  -.0476652   .0955402    -0.50   0.618    -.2
> 351032                                                                       
>           .1397728
           Secundaria 2ª etapa  |  -.0844434   .0960317    -0.88   0.379    -.2
> 728456                                                                       
>           .1039588
                          F.P.  |  -.0777768   .0954615    -0.81   0.415    -.2
> 650603                                                                       
>           .1095067
                    Superiores  |  -.0706074   .0961253    -0.73   0.463    -.2
> 591931                                                                       
>           .1179783
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0458809   .0420069     1.09   0.275    -.0
> 365314                                                                       
>           .1282932
    10.001 a 50.000 habitantes  |   .0087911   .0372741     0.24   0.814    -.0
> 643359                                                                       
>           .0819182
   50.001 a 100.000 habitantes  |  -.0030156   .0423119    -0.07   0.943    -.0
> 860262                                                                       
>            .079995
  100.001 a 400.000 habitantes  |  -.0140741   .0383239    -0.37   0.714    -.0
> 892606                                                                       
>           .0611125
400.001 a 1.000.000 habitantes  |  -.0484115   .0393186    -1.23   0.218    -.1
> 255497                                                                       
>           .0287267
   Más de 1.000.000 habitantes  |  -.1130065   .0455945    -2.48   0.013    -.2
> 024573                                                                       
>          -.0235557
                                |
                           CCAA |
                        Aragón  |  -.0255737   .0356046    -0.72   0.473    -.0
> 954254                                                                       
>           .0442779
      Asturias (Principado de)  |   .0555532   .0546532     1.02   0.310    -.0
> 516695                                                                       
>           .1627759
               Balears (Illes)  |   .0522362   .0517454     1.01   0.313    -.0
> 492817                                                                       
>           .1537541
                      Canarias  |  -.0625802   .0341828    -1.83   0.067    -.1
> 296425                                                                       
>           .0044821
            Castilla-La Mancha  |    .123993   .0595354     2.08   0.037      .
> 007192                                                                       
>           .2407939
               Castilla y León  |    .080115   .0552447     1.45   0.147    -.0
> 282681                                                                       
>           .1884981
                      Cataluña  |    .008411   .0353601     0.24   0.812     -.
> 060961                                                                       
>            .077783
          Comunitat Valenciana  |   -.054462   .0275927    -1.97   0.049    -.1
> 085953                                                                       
>          -.0003287
                   Extremadura  |   -.022675   .0435731    -0.52   0.603      -
> .10816                                                                       
>           .0628099
                       Galicia  |  -.0928719    .028652    -3.24   0.001    -.1
> 490836                                                                       
>          -.0366603
         Madrid (Comunidad de)  |   .0950696   .0414657     2.29   0.022     .0
> 137191                                                                       
>             .17642
            Murcia (Región de)  |  -.0653896   .0247502    -2.64   0.008    -.1
> 139464                                                                       
>          -.0168327
  Navarra (Comunidad Foral de)  |  -.0166679    .056288    -0.30   0.767    -.1
> 270979                                                                       
>            .093762
                    País Vasco  |  -.0607642   .0361503    -1.68   0.093    -.1
> 316865                                                                       
>           .0101581
                    Rioja (La)  |  -.0948211   .0260615    -3.64   0.000    -.1
> 459506                                                                       
>          -.0436917
    Ceuta (Ciudad Autónoma de)  |    .089495    .081713     1.10   0.274    -.0
> 708156                                                                       
>           .2498055
  Melilla (Ciudad Autónoma de)  |  -.0360957    .065935    -0.55   0.584    -.1
> 654519                                                                       
>           .0932604
                                |
                          _cons |    .173038   .1141977     1.52   0.130    -.0
> 510036                                                                       
>           .3970796
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,768
                                                F(3, 1764)        =       1.96
                                                Prob > F          =     0.1183
                                                R-squared         =     0.0048
                                                Root MSE          =     .30349

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0056632   .0153915    -0.37   0.713    -.0358506    .0
> 245242
           pp_dummy |  -.0195977   .0278462    -0.70   0.482    -.0742127    .0
> 350174
cabine_use_pp_dummy |   .1001546   .0449121     2.23   0.026     .0120681    .1
> 882411
              _cons |   .1006787   .0101319     9.94   0.000     .0808069    .1
> 205506
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,300
                                                F(44, 1255)       =       2.07
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0706
                                                Root MSE          =     .27195

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0281444   .0174485    -1.61   0.107    -.0
> 623758                                                                       
>           .0060871
                       pp_dummy |  -.0407179   .0302587    -1.35   0.179    -.1
> 000812                                                                       
>           .0186453
            cabine_use_pp_dummy |    .083916   .0455381     1.84   0.066    -.0
> 054232                                                                       
>           .1732551
                         female |   .0292827   .0156358     1.87   0.061    -.0
> 013926                                                                       
>           .0599579
                                |
                         income |
         Menos o igual a 300 €  |   .0201592   .0646147     0.31   0.755    -.1
> 066055                                                                       
>           .1469239
                De 301 a 600 €  |   .0774789   .0409606     1.89   0.059      -
> .00288                                                                       
>           .1578377
                De 601 a 900 €  |   -.000113   .0306618    -0.00   0.997    -.0
> 602671                                                                       
>            .060041
              De 901 a 1.200 €  |  -.0134802    .027502    -0.49   0.624    -.0
> 674352                                                                       
>           .0404748
            De 1.201 a 1.800 €  |   .0025243    .028149     0.09   0.929    -.0
> 526999                                                                       
>           .0577485
            De 1.801 a 2.400 €  |  -.0335851    .030479    -1.10   0.271    -.0
> 933805                                                                       
>           .0262102
            De 2.401 a 3.000 €  |  -.0204042   .0428844    -0.48   0.634    -.1
> 045371                                                                       
>           .0637288
            De 3.001 a 4.500 €  |   .0729006   .0683981     1.07   0.287    -.0
> 612866                                                                       
>           .2070879
            De 4.501 a 6.000 €  |  -.0870818   .0445283    -1.96   0.051      -
> .17444                                                                       
>           .0002763
                Más de 6.000 €  |  -.0801723   .0422369    -1.90   0.058     -.
> 163035                                                                       
>           .0026903
                                |
                            age |  -.0012772   .0031533    -0.41   0.686    -.0
> 074636                                                                       
>           .0049091
                         age_sq |   .0000188   .0000334     0.56   0.575    -.0
> 000468                                                                       
>           .0000844
                                |
                      education |
                      Primaria  |   -.056361   .0921189    -0.61   0.541    -.2
> 370851                                                                       
>            .124363
           Secundaria 1ª etapa  |  -.0195669   .0942068    -0.21   0.835     -.
> 204387                                                                       
>           .1652533
           Secundaria 2ª etapa  |  -.0680403   .0949222    -0.72   0.474     -.
> 254264                                                                       
>           .1181834
                          F.P.  |  -.0579542   .0941681    -0.62   0.538    -.2
> 426983                                                                       
>             .12679
                    Superiores  |  -.0596088   .0946576    -0.63   0.529    -.2
> 453133                                                                       
>           .1260957
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .054487   .0360198     1.51   0.131    -.0
> 161788                                                                       
>           .1251527
    10.001 a 50.000 habitantes  |    .023246   .0313824     0.74   0.459    -.0
> 383218                                                                       
>           .0848137
   50.001 a 100.000 habitantes  |   .0076522   .0362964     0.21   0.833    -.0
> 635561                                                                       
>           .0788604
  100.001 a 400.000 habitantes  |  -.0077825   .0326788    -0.24   0.812    -.0
> 718937                                                                       
>           .0563286
400.001 a 1.000.000 habitantes  |  -.0416054   .0351374    -1.18   0.237      -
> .11054                                                                       
>           .0273292
   Más de 1.000.000 habitantes  |  -.1038495   .0418533    -2.48   0.013    -.1
> 859597                                                                       
>          -.0217393
                                |
                           CCAA |
                        Aragón  |    -.02272   .0356972    -0.64   0.525    -.0
> 927528                                                                       
>           .0473128
      Asturias (Principado de)  |   .0515186   .0542307     0.95   0.342    -.0
> 548742                                                                       
>           .1579114
               Balears (Illes)  |   .0505497   .0519149     0.97   0.330    -.0
> 512999                                                                       
>           .1523994
                      Canarias  |  -.0578457   .0347633    -1.66   0.096    -.1
> 260462                                                                       
>           .0103549
                     Cantabria  |  -.0362831   .0362207    -1.00   0.317    -.1
> 073429                                                                       
>           .0347768
               Castilla y León  |   .0848624    .055507     1.53   0.127    -.0
> 240342                                                                       
>           .1937591
                      Cataluña  |  -.0006135   .0349608    -0.02   0.986    -.0
> 692016                                                                       
>           .0679745
          Comunitat Valenciana  |  -.0579626   .0276514    -2.10   0.036    -.1
> 122107                                                                       
>          -.0037145
                   Extremadura  |  -.0141933   .0431521    -0.33   0.742    -.0
> 988514                                                                       
>           .0704649
                       Galicia  |  -.0949335   .0285145    -3.33   0.001    -.1
> 508748                                                                       
>          -.0389922
         Madrid (Comunidad de)  |   .0905092   .0412973     2.19   0.029     .0
> 094898                                                                       
>           .1715285
            Murcia (Región de)  |  -.0627034   .0243273    -2.58   0.010    -.1
> 104302                                                                       
>          -.0149767
  Navarra (Comunidad Foral de)  |  -.0199467   .0559578    -0.36   0.722    -.1
> 297279                                                                       
>           .0898346
                    País Vasco  |  -.0650814    .036088    -1.80   0.072    -.1
> 358808                                                                       
>           .0057181
                    Rioja (La)  |  -.0911296   .0256025    -3.56   0.000    -.1
> 413581                                                                       
>          -.0409011
    Ceuta (Ciudad Autónoma de)  |   .0949799   .0815513     1.16   0.244     -.
> 065012                                                                       
>           .2549717
  Melilla (Ciudad Autónoma de)  |  -.0246175   .0632696    -0.39   0.697    -.1
> 487433                                                                       
>           .0995082
                                |
                          _cons |   .1484758   .1110819     1.34   0.182     -.
> 069451                                                                       
>           .3664026
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,784
                                                F(3, 1780)        =       1.67
                                                Prob > F          =     0.1720
                                                R-squared         =     0.0031
                                                Root MSE          =      .2958

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0187694    .014941    -1.26   0.209    -.0480732    .0
> 105345
           pp_dummy |  -.0336896   .0258506    -1.30   0.193    -.0843902    .0
> 170111
cabine_use_pp_dummy |   .0909364   .0418009     2.18   0.030     .0089524    .1
> 729204
              _cons |   .1032548   .0102056    10.12   0.000     .0832386     .
> 123271
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,302
                                                F(44, 1257)       =       2.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0738
                                                Root MSE          =     .27464

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0170972   .0175354    -0.98   0.330     -.
> 051499                                                                       
>           .0173047
                       pp_dummy |  -.0386735   .0300545    -1.29   0.198     -.
> 097636                                                                       
>           .0202889
            cabine_use_pp_dummy |   .0946733   .0461153     2.05   0.040     .0
> 042018                                                                       
>           .1851447
                         female |   .0242797   .0159217     1.52   0.128    -.0
> 069563                                                                       
>           .0555158
                                |
                         income |
         Menos o igual a 300 €  |   .0249551   .0639285     0.39   0.696    -.1
> 004631                                                                       
>           .1503734
                De 301 a 600 €  |   .0724101   .0404434     1.79   0.074    -.0
> 069339                                                                       
>           .1517541
                De 601 a 900 €  |   .0066161   .0302986     0.22   0.827    -.0
> 528252                                                                       
>           .0660574
              De 901 a 1.200 €  |   .0133192   .0283659     0.47   0.639    -.0
> 423305                                                                       
>            .068969
            De 1.201 a 1.800 €  |   .0066084   .0279728     0.24   0.813    -.0
> 482702                                                                       
>           .0614869
            De 1.801 a 2.400 €  |   -.037308   .0302116    -1.23   0.217    -.0
> 965787                                                                       
>           .0219627
            De 2.401 a 3.000 €  |  -.0273064   .0429411    -0.64   0.525    -.1
> 115505                                                                       
>           .0569378
            De 3.001 a 4.500 €  |   .0700549   .0689984     1.02   0.310    -.0
> 653099                                                                       
>           .2054196
            De 4.501 a 6.000 €  |  -.0849733   .0442648    -1.92   0.055    -.1
> 718144                                                                       
>           .0018677
                Más de 6.000 €  |  -.0809803   .0424338    -1.91   0.057    -.1
> 642292                                                                       
>           .0022687
                                |
                            age |  -.0012942     .00312    -0.41   0.678    -.0
> 074153                                                                       
>           .0048268
                         age_sq |   .0000173   .0000331     0.52   0.601    -.0
> 000476                                                                       
>           .0000822
                                |
                      education |
                      Primaria  |  -.1018374   .0914652    -1.11   0.266    -.2
> 812786                                                                       
>           .0776039
           Secundaria 1ª etapa  |  -.0491133   .0938121    -0.52   0.601    -.2
> 331589                                                                       
>           .1349323
           Secundaria 2ª etapa  |  -.0900164   .0942746    -0.95   0.340    -.2
> 749694                                                                       
>           .0949365
                          F.P.  |  -.0853004   .0937241    -0.91   0.363    -.2
> 691732                                                                       
>           .0985725
                    Superiores  |  -.0784929   .0942936    -0.83   0.405     -.
> 263483                                                                       
>           .1064972
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0818604   .0339535     2.41   0.016     .0
> 152485                                                                       
>           .1484722
    10.001 a 50.000 habitantes  |   .0486234   .0295574     1.65   0.100     -.
> 009364                                                                       
>           .1066107
   50.001 a 100.000 habitantes  |   .0442259   .0357313     1.24   0.216    -.0
> 258737                                                                       
>           .1143255
  100.001 a 400.000 habitantes  |   .0240678   .0305318     0.79   0.431    -.0
> 358311                                                                       
>           .0839666
400.001 a 1.000.000 habitantes  |  -.0133552   .0338513    -0.39   0.693    -.0
> 797664                                                                       
>           .0530559
   Más de 1.000.000 habitantes  |  -.0743771   .0401291    -1.85   0.064    -.1
> 531045                                                                       
>           .0043503
                                |
                           CCAA |
                        Aragón  |  -.0153516   .0357968    -0.43   0.668    -.0
> 855797                                                                       
>           .0548765
      Asturias (Principado de)  |   .0516072   .0542099     0.95   0.341    -.0
> 547446                                                                       
>            .157959
               Balears (Illes)  |   .0523085   .0515796     1.01   0.311     -.
> 048883                                                                       
>           .1535001
                      Canarias  |  -.0634566   .0339931    -1.87   0.062    -.1
> 301461                                                                       
>            .003233
                     Cantabria  |  -.0320337   .0365236    -0.88   0.381    -.1
> 036876                                                                       
>           .0396202
            Castilla-La Mancha  |   .1237922   .0599174     2.07   0.039     .0
> 062432                                                                       
>           .2413413
                      Cataluña  |   .0082161   .0350711     0.23   0.815    -.0
> 605882                                                                       
>           .0770203
          Comunitat Valenciana  |  -.0547942   .0275247    -1.99   0.047    -.1
> 087937                                                                       
>          -.0007947
                   Extremadura  |  -.0142075   .0429291    -0.33   0.741     -.
> 098428                                                                       
>           .0700131
                       Galicia  |  -.0934162   .0285347    -3.27   0.001    -.1
> 493972                                                                       
>          -.0374353
         Madrid (Comunidad de)  |    .091493   .0414613     2.21   0.028      .
> 010152                                                                       
>           .1728339
            Murcia (Región de)  |  -.0642187   .0245524    -2.62   0.009    -.1
> 123869                                                                       
>          -.0160506
  Navarra (Comunidad Foral de)  |  -.0145712   .0561334    -0.26   0.795    -.1
> 246965                                                                       
>           .0955542
                    País Vasco  |  -.0620027   .0371385    -1.67   0.095    -.1
> 348629                                                                       
>           .0108575
                    Rioja (La)  |  -.0912564   .0255317    -3.57   0.000    -.1
> 413458                                                                       
>          -.0411671
    Ceuta (Ciudad Autónoma de)  |   .0825015   .0816804     1.01   0.313    -.0
> 777434                                                                       
>           .2427464
  Melilla (Ciudad Autónoma de)  |  -.0414566    .065692    -0.63   0.528    -.1
> 703346                                                                       
>           .0874214
                                |
                          _cons |   .1388753   .1079654     1.29   0.199    -.0
> 729369                                                                       
>           .3506875
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,772
                                                F(3, 1768)        =       1.68
                                                Prob > F          =     0.1696
                                                R-squared         =     0.0035
                                                Root MSE          =     .29662

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0107881   .0150778    -0.72   0.474    -.0403603    .0
> 187842
           pp_dummy |  -.0292596   .0259824    -1.13   0.260     -.080219    .0
> 216998
cabine_use_pp_dummy |   .0944588   .0424811     2.22   0.026     .0111403    .1
> 777772
              _cons |    .099435   .0100704     9.87   0.000     .0796839    .1
> 191862
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,219
                                                F(43, 1174)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0852
                                                Root MSE          =     .28152

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0102998   .0184423    -0.56   0.577    -.0
> 464834                                                                       
>           .0258838
                       pp_dummy |  -.0346381   .0309949    -1.12   0.264    -.0
> 954498                                                                       
>           .0261735
            cabine_use_pp_dummy |   .0999594   .0469139     2.13   0.033      .
> 007915                                                                       
>           .1920037
                         female |   .0349565   .0166263     2.10   0.036     .0
> 023359                                                                       
>            .067577
                                |
                         income |
         Menos o igual a 300 €  |   .0240631   .0666416     0.36   0.718    -.1
> 066868                                                                       
>           .1548131
                De 301 a 600 €  |    .081523   .0428197     1.90   0.057    -.0
> 024887                                                                       
>           .1655346
                De 601 a 900 €  |   .0099354   .0317208     0.31   0.754    -.0
> 523003                                                                       
>           .0721712
              De 901 a 1.200 €  |   .0125316   .0296891     0.42   0.673     -.
> 045718                                                                       
>           .0707813
            De 1.201 a 1.800 €  |   .0012145    .029339     0.04   0.967    -.0
> 563483                                                                       
>           .0587773
            De 1.801 a 2.400 €  |  -.0260041   .0323594    -0.80   0.422    -.0
> 894929                                                                       
>           .0374846
            De 2.401 a 3.000 €  |  -.0128428   .0469871    -0.27   0.785    -.1
> 050309                                                                       
>           .0793453
            De 3.001 a 4.500 €  |   .0365215   .0612693     0.60   0.551    -.0
> 836881                                                                       
>           .1567311
            De 4.501 a 6.000 €  |  -.0139122   .0527299    -0.26   0.792    -.1
> 173675                                                                       
>           .0895431
                Más de 6.000 €  |  -.0763658   .0444741    -1.72   0.086    -.1
> 636234                                                                       
>           .0108918
                                |
                            age |   .0004043   .0031345     0.13   0.897    -.0
> 057456                                                                       
>           .0065543
                         age_sq |  -3.61e-06    .000032    -0.11   0.910    -.0
> 000664                                                                       
>           .0000592
                                |
                      education |
                      Primaria  |  -.0902325   .1029793    -0.88   0.381    -.2
> 922766                                                                       
>           .1118116
           Secundaria 1ª etapa  |  -.0652334   .1049506    -0.62   0.534    -.2
> 711451                                                                       
>           .1406783
           Secundaria 2ª etapa  |  -.1196633    .104874    -1.14   0.254    -.3
> 254247                                                                       
>           .0860981
                          F.P.  |  -.1124061   .1041232    -1.08   0.281    -.3
> 166945                                                                       
>           .0918822
                    Superiores  |  -.1147274   .1049364    -1.09   0.274    -.3
> 206111                                                                       
>           .0911564
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0511324   .0416518     1.23   0.220    -.0
> 305879                                                                       
>           .1328527
    10.001 a 50.000 habitantes  |  -.0038217   .0367131    -0.10   0.917    -.0
> 758523                                                                       
>           .0682089
   50.001 a 100.000 habitantes  |  -.0039475   .0420342    -0.09   0.925    -.0
> 864181                                                                       
>           .0785231
  100.001 a 400.000 habitantes  |  -.0201101   .0389344    -0.52   0.606    -.0
> 964989                                                                       
>           .0562787
400.001 a 1.000.000 habitantes  |  -.0478645   .0396535    -1.21   0.228    -.1
> 256641                                                                       
>           .0299352
   Más de 1.000.000 habitantes  |   -.159371   .0613802    -2.60   0.010    -.2
> 797981                                                                       
>          -.0389438
                                |
                           CCAA |
                        Aragón  |  -.0226508   .0359868    -0.63   0.529    -.0
> 932564                                                                       
>           .0479549
      Asturias (Principado de)  |   .0584786   .0541047     1.08   0.280    -.0
> 476742                                                                       
>           .1646314
               Balears (Illes)  |   .0564345   .0521363     1.08   0.279    -.0
> 458562                                                                       
>           .1587252
                      Canarias  |  -.0631442   .0346428    -1.82   0.069    -.1
> 311128                                                                       
>           .0048245
                     Cantabria  |  -.0342099   .0369628    -0.93   0.355    -.1
> 067304                                                                       
>           .0383106
            Castilla-La Mancha  |   .1280956   .0596559     2.15   0.032     .0
> 110515                                                                       
>           .2451398
               Castilla y León  |   .0837334   .0549721     1.52   0.128    -.0
> 241212                                                                       
>            .191588
          Comunitat Valenciana  |  -.0517438   .0278952    -1.85   0.064    -.1
> 064738                                                                       
>           .0029862
                   Extremadura  |  -.0247952   .0440135    -0.56   0.573    -.1
> 111491                                                                       
>           .0615588
                       Galicia  |  -.0906421   .0287897    -3.15   0.002    -.1
> 471271                                                                       
>          -.0341571
         Madrid (Comunidad de)  |   .1180427   .0462802     2.55   0.011     .0
> 272416                                                                       
>           .2088437
            Murcia (Región de)  |  -.0599868   .0248398    -2.41   0.016    -.1
> 087221                                                                       
>          -.0112515
  Navarra (Comunidad Foral de)  |  -.0109971   .0555235    -0.20   0.843    -.1
> 199334                                                                       
>           .0979392
                    País Vasco  |  -.0531878   .0360395    -1.48   0.140    -.1
> 238969                                                                       
>           .0175212
                    Rioja (La)  |  -.0875439   .0261015    -3.35   0.001    -.1
> 387547                                                                       
>          -.0363331
    Ceuta (Ciudad Autónoma de)  |   .0925475   .0808197     1.15   0.252    -.0
> 660196                                                                       
>           .2511146
  Melilla (Ciudad Autónoma de)  |  -.0380238   .0643763    -0.59   0.555    -.1
> 643293                                                                       
>           .0882817
                                |
                          _cons |   .1622129   .1198321     1.35   0.176    -.0
> 728962                                                                       
>            .397322
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,585
                                                F(3, 1581)        =       2.43
                                                Prob > F          =     0.0636
                                                R-squared         =     0.0055
                                                Root MSE          =     .31056

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0170324   .0167423    -1.02   0.309    -.0498719    .0
> 158071
           pp_dummy |  -.0403417    .027609    -1.46   0.144    -.0944959    .0
> 138124
cabine_use_pp_dummy |   .1182182   .0440299     2.68   0.007     .0318551    .2
> 045813
              _cons |    .113069   .0121504     9.31   0.000     .0892364    .1
> 369017
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,231
                                                F(44, 1186)       =       2.32
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0812
                                                Root MSE          =     .28641

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0116537   .0191102    -0.61   0.542    -.0
> 491472                                                                       
>           .0258398
                       pp_dummy |  -.0306813    .032441    -0.95   0.344    -.0
> 943295                                                                       
>            .032967
            cabine_use_pp_dummy |   .1033001   .0494974     2.09   0.037      .
> 006188                                                                       
>           .2004122
                         female |   .0267066   .0169947     1.57   0.116    -.0
> 066365                                                                       
>           .0600497
                                |
                         income |
         Menos o igual a 300 €  |   .0334635   .0728549     0.46   0.646    -.1
> 094753                                                                       
>           .1764024
                De 301 a 600 €  |   .1006484   .0460654     2.18   0.029     .0
> 102696                                                                       
>           .1910272
                De 601 a 900 €  |   .0188939   .0323187     0.58   0.559    -.0
> 445143                                                                       
>           .0823021
              De 901 a 1.200 €  |   .0091147   .0294347     0.31   0.757    -.0
> 486352                                                                       
>           .0668646
            De 1.201 a 1.800 €  |    .005702   .0298546     0.19   0.849    -.0
> 528717                                                                       
>           .0642758
            De 1.801 a 2.400 €  |  -.0338609   .0320373    -1.06   0.291    -.0
> 967169                                                                       
>           .0289952
            De 2.401 a 3.000 €  |  -.0213138   .0456699    -0.47   0.641    -.1
> 109166                                                                       
>           .0682889
            De 3.001 a 4.500 €  |    .075473   .0702653     1.07   0.283    -.0
> 623852                                                                       
>           .2133312
            De 4.501 a 6.000 €  |  -.0625799   .0510059    -1.23   0.220    -.1
> 626517                                                                       
>           .0374919
                Más de 6.000 €  |  -.0847928   .0463361    -1.83   0.068    -.1
> 757026                                                                       
>            .006117
                                |
                            age |  -.0009454   .0034135    -0.28   0.782    -.0
> 076426                                                                       
>           .0057517
                         age_sq |   .0000145   .0000362     0.40   0.690    -.0
> 000566                                                                       
>           .0000856
                                |
                      education |
                      Primaria  |  -.0288695    .085417    -0.34   0.735    -.1
> 964547                                                                       
>           .1387157
           Secundaria 1ª etapa  |   .0099776   .0878336     0.11   0.910    -.1
> 623488                                                                       
>           .1823041
           Secundaria 2ª etapa  |  -.0363124   .0882971    -0.41   0.681    -.2
> 095483                                                                       
>           .1369236
                          F.P.  |  -.0264153   .0878092    -0.30   0.764     -.
> 198694                                                                       
>           .1458634
                    Superiores  |  -.0322777   .0886004    -0.36   0.716    -.2
> 061087                                                                       
>           .1415533
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0571494   .0393753     1.45   0.147    -.0
> 201035                                                                       
>           .1344023
    10.001 a 50.000 habitantes  |   .0247553   .0350608     0.71   0.480    -.0
> 440329                                                                       
>           .0935434
   50.001 a 100.000 habitantes  |   .0091124   .0412361     0.22   0.825    -.0
> 717914                                                                       
>           .0900163
  100.001 a 400.000 habitantes  |  -.0137307    .035433    -0.39   0.698     -.
> 083249                                                                       
>           .0557876
400.001 a 1.000.000 habitantes  |  -.0634138   .0383293    -1.65   0.098    -.1
> 386147                                                                       
>           .0117871
   Más de 1.000.000 habitantes  |  -.1018593   .0439927    -2.32   0.021    -.1
> 881716                                                                       
>          -.0155471
                                |
                           CCAA |
                        Aragón  |  -.0149753   .0356157    -0.42   0.674    -.0
> 848521                                                                       
>           .0549015
      Asturias (Principado de)  |   .0566002   .0539595     1.05   0.294    -.0
> 492666                                                                       
>            .162467
               Balears (Illes)  |   .0635848   .0516554     1.23   0.219    -.0
> 377614                                                                       
>           .1649309
                      Canarias  |  -.0678696   .0352074    -1.93   0.054    -.1
> 369454                                                                       
>           .0012062
                     Cantabria  |  -.0407247   .0367149    -1.11   0.268    -.1
> 127581                                                                       
>           .0313088
            Castilla-La Mancha  |   .1225611   .0601756     2.04   0.042     .0
> 044985                                                                       
>           .2406236
               Castilla y León  |   .0806058   .0554152     1.45   0.146     -.
> 028117                                                                       
>           .1893285
                      Cataluña  |   .0073939   .0356269     0.21   0.836     -.
> 062505                                                                       
>           .0772927
                   Extremadura  |  -.0262186   .0439929    -0.60   0.551    -.1
> 125312                                                                       
>           .0600941
                       Galicia  |  -.0987711   .0287671    -3.43   0.001    -.1
> 552111                                                                       
>          -.0423312
         Madrid (Comunidad de)  |    .096082    .041833     2.30   0.022      .
> 014007                                                                       
>            .178157
            Murcia (Región de)  |  -.0607195   .0247508    -2.45   0.014    -.1
> 092797                                                                       
>          -.0121593
  Navarra (Comunidad Foral de)  |  -.0185933     .05599    -0.33   0.740    -.1
> 284439                                                                       
>           .0912572
                    País Vasco  |  -.0612167   .0367063    -1.67   0.096    -.1
> 332333                                                                       
>           .0107998
                    Rioja (La)  |  -.0937891   .0270264    -3.47   0.001    -.1
> 468139                                                                       
>          -.0407643
    Ceuta (Ciudad Autónoma de)  |   .0854874   .0816541     1.05   0.295    -.0
> 747153                                                                       
>             .24569
  Melilla (Ciudad Autónoma de)  |  -.0412468   .0649403    -0.64   0.525    -.1
> 686575                                                                       
>           .0861639
                                |
                          _cons |   .0964848   .1083843     0.89   0.374    -.1
> 161617                                                                       
>           .3091312
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,706
                                                F(3, 1702)        =       2.26
                                                Prob > F          =     0.0802
                                                R-squared         =     0.0057
                                                Root MSE          =     .30967

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0059318   .0160066    -0.37   0.711    -.0373264    .0
> 254628
           pp_dummy |  -.0243692    .028015    -0.87   0.384    -.0793166    .0
> 305783
cabine_use_pp_dummy |   .1123507   .0460652     2.44   0.015     .0220003    .2
> 027011
              _cons |   .1054502   .0105844     9.96   0.000     .0846905      
> .12621
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,291
                                                F(43, 1246)       =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0800
                                                Root MSE          =      .2792

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0128609   .0175844    -0.73   0.465    -.0
> 473592                                                                       
>           .0216375
                       pp_dummy |   -.037702   .0298694    -1.26   0.207    -.0
> 963018                                                                       
>           .0208978
            cabine_use_pp_dummy |   .1151371   .0481271     2.39   0.017      .
> 020718                                                                       
>           .2095563
                         female |   .0313969   .0159884     1.96   0.050     .0
> 000297                                                                       
>           .0627641
                                |
                         income |
         Menos o igual a 300 €  |   .0411508   .0717074     0.57   0.566    -.0
> 995298                                                                       
>           .1818314
                De 301 a 600 €  |   .0787635   .0416954     1.89   0.059    -.0
> 030374                                                                       
>           .1605645
                De 601 a 900 €  |   .0073525   .0310058     0.24   0.813    -.0
> 534768                                                                       
>           .0681818
              De 901 a 1.200 €  |   .0150057   .0293616     0.51   0.609    -.0
> 425979                                                                       
>           .0726094
            De 1.201 a 1.800 €  |   .0017405   .0280678     0.06   0.951    -.0
> 533248                                                                       
>           .0568058
            De 1.801 a 2.400 €  |   -.036145   .0306682    -1.18   0.239     -.
> 096312                                                                       
>            .024022
            De 2.401 a 3.000 €  |  -.0255873   .0433873    -0.59   0.555    -.1
> 107076                                                                       
>           .0595329
            De 3.001 a 4.500 €  |   .0607633   .0677047     0.90   0.370    -.0
> 720646                                                                       
>           .1935912
            De 4.501 a 6.000 €  |   -.118411    .043577    -2.72   0.007    -.2
> 039034                                                                       
>          -.0329186
                Más de 6.000 €  |  -.0686039   .0418398    -1.64   0.101    -.1
> 506881                                                                       
>           .0134803
                                |
                            age |  -.0007601   .0031571    -0.24   0.810    -.0
> 069539                                                                       
>           .0054337
                         age_sq |    .000013   .0000333     0.39   0.697    -.0
> 000524                                                                       
>           .0000784
                                |
                      education |
                      Primaria  |  -.0289304   .0855439    -0.34   0.735    -.1
> 967563                                                                       
>           .1388955
           Secundaria 1ª etapa  |   .0120055   .0874269     0.14   0.891    -.1
> 595146                                                                       
>           .1835257
           Secundaria 2ª etapa  |  -.0485093   .0873921    -0.56   0.579    -.2
> 199612                                                                       
>           .1229427
                          F.P.  |  -.0339436   .0869884    -0.39   0.696    -.2
> 046035                                                                       
>           .1367164
                    Superiores  |  -.0282611   .0870024    -0.32   0.745    -.1
> 989485                                                                       
>           .1424263
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0275879   .0397686     0.69   0.488     -.
> 050433                                                                       
>           .1056088
    10.001 a 50.000 habitantes  |   .0064697   .0362988     0.18   0.859    -.0
> 647437                                                                       
>           .0776832
   50.001 a 100.000 habitantes  |  -.0183069   .0403441    -0.45   0.650    -.0
> 974569                                                                       
>            .060843
  100.001 a 400.000 habitantes  |  -.0200312   .0379051    -0.53   0.597     -.
> 094396                                                                       
>           .0543336
400.001 a 1.000.000 habitantes  |   -.054359   .0387299    -1.40   0.161     -.
> 130342                                                                       
>           .0216239
   Más de 1.000.000 habitantes  |  -.1206523   .0451083    -2.67   0.008    -.2
> 091489                                                                       
>          -.0321558
                                |
                           CCAA |
                        Aragón  |  -.0257935   .0356671    -0.72   0.470    -.0
> 957677                                                                       
>           .0441807
      Asturias (Principado de)  |   .0573055   .0536175     1.07   0.285     -.
> 047885                                                                       
>            .162496
               Balears (Illes)  |   .0520978   .0513123     1.02   0.310    -.0
> 485702                                                                       
>           .1527658
                      Canarias  |  -.0684425   .0346333    -1.98   0.048    -.1
> 363885                                                                       
>          -.0004965
                     Cantabria  |  -.0372997   .0367135    -1.02   0.310    -.1
> 093269                                                                       
>           .0347275
            Castilla-La Mancha  |    .126509   .0596802     2.12   0.034     .0
> 094243                                                                       
>           .2435938
               Castilla y León  |   .0818377   .0548578     1.49   0.136    -.0
> 257863                                                                       
>           .1894616
                      Cataluña  |   .0090557   .0354348     0.26   0.798    -.0
> 604627                                                                       
>           .0785742
          Comunitat Valenciana  |  -.0555254   .0278547    -1.99   0.046    -.1
> 101727                                                                       
>          -.0008781
                       Galicia  |  -.0926734   .0284231    -3.26   0.001    -.1
> 484359                                                                       
>           -.036911
         Madrid (Comunidad de)  |    .098651    .041658     2.37   0.018     .0
> 169235                                                                       
>           .1803786
            Murcia (Región de)  |  -.0673656   .0246615    -2.73   0.006    -.1
> 157482                                                                       
>           -.018983
  Navarra (Comunidad Foral de)  |  -.0143342   .0559152    -0.26   0.798    -.1
> 240325                                                                       
>            .095364
                    País Vasco  |  -.0614091   .0358701    -1.71   0.087    -.1
> 317815                                                                       
>           .0089633
                    Rioja (La)  |  -.0956822   .0261621    -3.66   0.000    -.1
> 470089                                                                       
>          -.0443556
    Ceuta (Ciudad Autónoma de)  |   .0960706   .0810361     1.19   0.236    -.0
> 629117                                                                       
>           .2550528
  Melilla (Ciudad Autónoma de)  |  -.0305512    .065522    -0.47   0.641    -.1
> 590969                                                                       
>           .0979945
                                |
                          _cons |   .1102741   .1056207     1.04   0.297    -.0
> 969399                                                                       
>            .317488
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,775
                                                F(3, 1771)        =       2.33
                                                Prob > F          =     0.0727
                                                R-squared         =     0.0058
                                                Root MSE          =     .30282

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0089408   .0153069    -0.58   0.559    -.0389624    .0
> 210807
           pp_dummy |  -.0239763   .0268406    -0.89   0.372    -.0766188    .0
> 286662
cabine_use_pp_dummy |   .1138943   .0451619     2.52   0.012      .025318    .2
> 024706
              _cons |   .1015625   .0101029    10.05   0.000     .0817476    .1
> 213774
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,294
                                                F(44, 1249)       =       2.33
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0763
                                                Root MSE          =     .28482

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0181106   .0183702    -0.99   0.324    -.0
> 541504                                                                       
>           .0179292
                       pp_dummy |  -.0390344   .0314794    -1.24   0.215    -.1
> 007928                                                                       
>            .022724
            cabine_use_pp_dummy |   .1071485    .047698     2.25   0.025     .0
> 135714                                                                       
>           .2007255
                         female |   .0282403   .0164409     1.72   0.086    -.0
> 040146                                                                       
>           .0604952
                                |
                         income |
         Menos o igual a 300 €  |   .0264711   .0661431     0.40   0.689    -.1
> 032927                                                                       
>           .1562349
                De 301 a 600 €  |   .0858652   .0435081     1.97   0.049     .0
> 005081                                                                       
>           .1712223
                De 601 a 900 €  |    .003881   .0318701     0.12   0.903    -.0
> 586439                                                                       
>           .0664059
              De 901 a 1.200 €  |   .0129611   .0299102     0.43   0.665    -.0
> 457187                                                                       
>           .0716408
            De 1.201 a 1.800 €  |   .0073722     .02933     0.25   0.802    -.0
> 501694                                                                       
>           .0649138
            De 1.801 a 2.400 €  |  -.0386218    .031377    -1.23   0.219    -.1
> 001792                                                                       
>           .0229356
            De 2.401 a 3.000 €  |  -.0263584   .0438921    -0.60   0.548    -.1
> 124687                                                                       
>            .059752
            De 3.001 a 4.500 €  |   .0625142   .0702435     0.89   0.374    -.0
> 752941                                                                       
>           .2003226
            De 4.501 a 6.000 €  |  -.0756438   .0474633    -1.59   0.111    -.1
> 687603                                                                       
>           .0174727
                Más de 6.000 €  |  -.0770828     .04362    -1.77   0.077    -.1
> 626594                                                                       
>           .0084937
                                |
                            age |    -.00155   .0033495    -0.46   0.644    -.0
> 081213                                                                       
>           .0050213
                         age_sq |   .0000211   .0000357     0.59   0.555     -.
> 000049                                                                       
>           .0000911
                                |
                      education |
                      Primaria  |  -.0924696   .1006346    -0.92   0.358    -.2
> 899011                                                                       
>           .1049619
           Secundaria 1ª etapa  |  -.0562333   .1028832    -0.55   0.585    -.2
> 580761                                                                       
>           .1456096
           Secundaria 2ª etapa  |  -.1052195   .1033769    -1.02   0.309    -.3
> 080309                                                                       
>            .097592
                          F.P.  |    -.09848    .102534    -0.96   0.337    -.2
> 996379                                                                       
>           .1026779
                    Superiores  |  -.0889031   .1034717    -0.86   0.390    -.2
> 919006                                                                       
>           .1140943
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0624492   .0393385     1.59   0.113    -.0
> 147276                                                                       
>            .139626
    10.001 a 50.000 habitantes  |   .0185809   .0342612     0.54   0.588    -.0
> 486349                                                                       
>           .0857967
   50.001 a 100.000 habitantes  |    .007524   .0393546     0.19   0.848    -.0
> 696843                                                                       
>           .0847324
  100.001 a 400.000 habitantes  |  -.0069389   .0354439    -0.20   0.845     -.
> 076475                                                                       
>           .0625972
400.001 a 1.000.000 habitantes  |  -.0382554   .0372258    -1.03   0.304    -.1
> 112874                                                                       
>           .0347766
   Más de 1.000.000 habitantes  |  -.1039425   .0435939    -2.38   0.017    -.1
> 894679                                                                       
>          -.0184171
                                |
                           CCAA |
                        Aragón  |  -.0212474   .0358163    -0.59   0.553    -.0
> 915142                                                                       
>           .0490195
      Asturias (Principado de)  |   .0573999   .0542986     1.06   0.291    -.0
> 491266                                                                       
>           .1639263
               Balears (Illes)  |   .0528803   .0517636     1.02   0.307    -.0
> 486729                                                                       
>           .1544335
                      Canarias  |  -.0588842   .0344932    -1.71   0.088    -.1
> 265552                                                                       
>           .0087868
                     Cantabria  |   -.035249   .0366246    -0.96   0.336    -.1
> 071015                                                                       
>           .0366036
            Castilla-La Mancha  |   .1268382    .059749     2.12   0.034     .0
> 096188                                                                       
>           .2440576
               Castilla y León  |   .0843794   .0553921     1.52   0.128    -.0
> 242924                                                                       
>           .1930511
                      Cataluña  |   .0089425   .0353168     0.25   0.800    -.0
> 603444                                                                       
>           .0782294
          Comunitat Valenciana  |  -.0547859   .0276434    -1.98   0.048    -.1
> 090186                                                                       
>          -.0005533
                   Extremadura  |  -.0211475   .0432316    -0.49   0.625    -.1
> 059621                                                                       
>           .0636671
         Madrid (Comunidad de)  |   .0970896   .0415836     2.33   0.020     .0
> 155081                                                                       
>           .1786711
            Murcia (Región de)  |  -.0621402   .0248077    -2.50   0.012    -.1
> 108096                                                                       
>          -.0134708
  Navarra (Comunidad Foral de)  |  -.0172572   .0561857    -0.31   0.759    -.1
> 274859                                                                       
>           .0929714
                    País Vasco  |  -.0582703   .0364647    -1.60   0.110    -.1
> 298091                                                                       
>           .0132685
                    Rioja (La)  |  -.0900588   .0261674    -3.44   0.001    -.1
> 413957                                                                       
>           -.038722
    Ceuta (Ciudad Autónoma de)  |   .0921661   .0814999     1.13   0.258    -.0
> 677258                                                                       
>            .252058
  Melilla (Ciudad Autónoma de)  |  -.0322337    .064595    -0.50   0.618    -.1
> 589603                                                                       
>           .0944929
                                |
                          _cons |     .17488   .1194024     1.46   0.143    -.0
> 593714                                                                       
>           .4091315
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,764
                                                F(3, 1760)        =       2.03
                                                Prob > F          =     0.1080
                                                R-squared         =     0.0048
                                                Root MSE          =     .30527

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0094531   .0155015    -0.61   0.542    -.0398564    .0
> 209501
           pp_dummy |  -.0225636   .0279072    -0.81   0.419    -.0772983    .0
> 321712
cabine_use_pp_dummy |   .1022851   .0442322     2.31   0.021     .0155319    .1
> 890383
              _cons |   .1036446   .0102982    10.06   0.000     .0834468    .1
> 238425
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,204
                                                F(44, 1159)       =       2.17
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0832
                                                Root MSE          =     .26932

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0135077   .0178912    -0.75   0.450    -.0
> 486104                                                                       
>           .0215951
                       pp_dummy |   -.029964   .0295878    -1.01   0.311    -.0
> 880156                                                                       
>           .0280876
            cabine_use_pp_dummy |   .0826409   .0452206     1.83   0.068    -.0
> 060825                                                                       
>           .1713643
                         female |   .0211498   .0162025     1.31   0.192    -.0
> 106398                                                                       
>           .0529394
                                |
                         income |
         Menos o igual a 300 €  |   .0477586   .0686997     0.70   0.487     -.
> 087031                                                                       
>           .1825482
                De 301 a 600 €  |   .0726167   .0405683     1.79   0.074    -.0
> 069788                                                                       
>           .1522122
                De 601 a 900 €  |   .0060408   .0307707     0.20   0.844    -.0
> 543317                                                                       
>           .0664134
              De 901 a 1.200 €  |    .021493   .0297494     0.72   0.470    -.0
> 368757                                                                       
>           .0798618
            De 1.201 a 1.800 €  |  -.0072343   .0280372    -0.26   0.796    -.0
> 622437                                                                       
>           .0477751
            De 1.801 a 2.400 €  |  -.0554456    .030339    -1.83   0.068    -.1
> 149712                                                                       
>           .0040799
            De 2.401 a 3.000 €  |  -.0809385   .0300379    -2.69   0.007    -.1
> 398733                                                                       
>          -.0220037
            De 3.001 a 4.500 €  |  -.0178209   .0541746    -0.33   0.742    -.1
> 241123                                                                       
>           .0884704
            De 4.501 a 6.000 €  |   -.083319   .0448562    -1.86   0.063    -.1
> 713275                                                                       
>           .0046896
                Más de 6.000 €  |  -.0591734   .0409093    -1.45   0.148    -.1
> 394381                                                                       
>           .0210912
                                |
                            age |  -.0000201   .0032648    -0.01   0.995    -.0
> 064257                                                                       
>           .0063854
                         age_sq |   9.16e-06   .0000348     0.26   0.793    -.0
> 000592                                                                       
>           .0000775
                                |
                      education |
                      Primaria  |  -.0791977   .0932193    -0.85   0.396    -.2
> 620951                                                                       
>           .1036998
           Secundaria 1ª etapa  |  -.0228123   .0960587    -0.24   0.812    -.2
> 112807                                                                       
>           .1656561
           Secundaria 2ª etapa  |  -.0821099   .0964361    -0.85   0.395    -.2
> 713187                                                                       
>           .1070989
                          F.P.  |  -.0574161   .0959997    -0.60   0.550    -.2
> 457687                                                                       
>           .1309365
                    Superiores  |  -.0511592   .0964339    -0.53   0.596    -.2
> 403638                                                                       
>           .1380453
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0552865    .037469     1.48   0.140    -.0
> 182282                                                                       
>           .1288011
    10.001 a 50.000 habitantes  |   .0207947   .0331877     0.63   0.531      -
> .04432                                                                       
>           .0859093
   50.001 a 100.000 habitantes  |  -.0127802   .0381231    -0.34   0.738    -.0
> 875782                                                                       
>           .0620178
  100.001 a 400.000 habitantes  |   -.017656   .0341967    -0.52   0.606    -.0
> 847503                                                                       
>           .0494383
400.001 a 1.000.000 habitantes  |  -.0416648   .0365614    -1.14   0.255    -.1
> 133988                                                                       
>           .0300691
   Más de 1.000.000 habitantes  |  -.0534507   .0466519    -1.15   0.252    -.1
> 449823                                                                       
>           .0380809
                                |
                           CCAA |
                        Aragón  |  -.0238865   .0359758    -0.66   0.507    -.0
> 944715                                                                       
>           .0466986
      Asturias (Principado de)  |   .0593529   .0537858     1.10   0.270    -.0
> 461755                                                                       
>           .1648814
               Balears (Illes)  |   .0501138   .0509462     0.98   0.325    -.0
> 498433                                                                       
>           .1500709
                      Canarias  |  -.0673328   .0345839    -1.95   0.052    -.1
> 351868                                                                       
>           .0005213
                     Cantabria  |  -.0377502   .0364425    -1.04   0.300    -.1
> 092509                                                                       
>           .0337505
            Castilla-La Mancha  |   .1262357    .059327     2.13   0.034     .0
> 098354                                                                       
>            .242636
               Castilla y León  |   .0879436   .0552232     1.59   0.112    -.0
> 204049                                                                       
>           .1962921
                      Cataluña  |  -.0048501   .0370258    -0.13   0.896    -.0
> 774953                                                                       
>           .0677951
          Comunitat Valenciana  |  -.0568389   .0276208    -2.06   0.040    -.1
> 110313                                                                       
>          -.0026466
                   Extremadura  |  -.0240854   .0438202    -0.55   0.583    -.1
> 100613                                                                       
>           .0618905
                       Galicia  |   -.100017    .028573    -3.50   0.000    -.1
> 560776                                                                       
>          -.0439564
            Murcia (Región de)  |   -.066312   .0244437    -2.71   0.007    -.1
> 142708                                                                       
>          -.0183532
  Navarra (Comunidad Foral de)  |  -.0193244   .0558366    -0.35   0.729    -.1
> 288765                                                                       
>           .0902276
                    País Vasco  |  -.0640538   .0364031    -1.76   0.079    -.1
> 354772                                                                       
>           .0073696
                    Rioja (La)  |  -.0844475    .025638    -3.29   0.001    -.1
> 347496                                                                       
>          -.0341455
    Ceuta (Ciudad Autónoma de)  |   .1045773   .0811674     1.29   0.198    -.0
> 546741                                                                       
>           .2638287
  Melilla (Ciudad Autónoma de)  |   -.023349   .0650073    -0.36   0.720    -.1
> 508941                                                                       
>           .1041962
                                |
                          _cons |    .116929   .1129541     1.04   0.301    -.1
> 046884                                                                       
>           .3385463
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,620
                                                F(3, 1616)        =       1.51
                                                Prob > F          =     0.2092
                                                R-squared         =     0.0040
                                                Root MSE          =     .30059

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |    -.00639   .0156867    -0.41   0.684    -.0371584    .0
> 243784
           pp_dummy |   -.009666   .0338044    -0.29   0.775     -.075971    .0
> 566391
cabine_use_pp_dummy |   .0807453   .0477886     1.69   0.091    -.0129888    .1
> 744795
              _cons |   .0982736   .0108616     9.05   0.000     .0769692    .1
> 195779
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,289
                                                F(44, 1244)       =       2.28
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0756
                                                Root MSE          =     .28544

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |    -.01394   .0181876    -0.77   0.444    -.0
> 496218                                                                       
>           .0217418
                       pp_dummy |  -.0389873   .0305776    -1.28   0.203    -.0
> 989767                                                                       
>           .0210021
            cabine_use_pp_dummy |   .1154803   .0490526     2.35   0.019     .0
> 192454                                                                       
>           .2117153
                         female |   .0273074   .0165812     1.65   0.100    -.0
> 052227                                                                       
>           .0598375
                                |
                         income |
         Menos o igual a 300 €  |  -.0075836   .0591686    -0.13   0.898     -.
> 123665                                                                       
>           .1084977
                De 301 a 600 €  |    .081676   .0421082     1.94   0.053    -.0
> 009349                                                                       
>           .1642869
                De 601 a 900 €  |   .0091515   .0322182     0.28   0.776    -.0
> 540565                                                                       
>           .0723594
              De 901 a 1.200 €  |    .010435   .0296767     0.35   0.725     -.
> 047787                                                                       
>            .068657
            De 1.201 a 1.800 €  |   .0054341   .0296673     0.18   0.855    -.0
> 527694                                                                       
>           .0636375
            De 1.801 a 2.400 €  |  -.0434636   .0321507    -1.35   0.177    -.1
> 065391                                                                       
>           .0196119
            De 2.401 a 3.000 €  |  -.0307719   .0444567    -0.69   0.489    -.1
> 179902                                                                       
>           .0564464
            De 3.001 a 4.500 €  |   .0653574    .072776     0.90   0.369    -.0
> 774198                                                                       
>           .2081346
            De 4.501 a 6.000 €  |  -.0789947   .0483534    -1.63   0.103    -.1
> 738579                                                                       
>           .0158684
                Más de 6.000 €  |  -.0976732   .0442392    -2.21   0.027    -.1
> 844649                                                                       
>          -.0108816
                                |
                            age |  -.0009528   .0032565    -0.29   0.770    -.0
> 073417                                                                       
>           .0054361
                         age_sq |   .0000145   .0000344     0.42   0.672    -.0
> 000529                                                                       
>           .0000819
                                |
                      education |
                      Primaria  |   -.085104   .0962617    -0.88   0.377    -.2
> 739571                                                                       
>           .1037492
           Secundaria 1ª etapa  |  -.0467077   .0983078    -0.48   0.635    -.2
> 395751                                                                       
>           .1461598
           Secundaria 2ª etapa  |  -.0949811   .0986717    -0.96   0.336    -.2
> 885624                                                                       
>           .0986003
                          F.P.  |  -.0888692   .0981845    -0.91   0.366    -.2
> 814947                                                                       
>           .1037563
                    Superiores  |   -.079201   .0987006    -0.80   0.422    -.2
> 728391                                                                       
>           .1144371
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0588685   .0372667     1.58   0.114     -.
> 014244                                                                       
>            .131981
    10.001 a 50.000 habitantes  |   .0228202   .0329606     0.69   0.489    -.0
> 418443                                                                       
>           .0874846
   50.001 a 100.000 habitantes  |   .0070025    .038032     0.18   0.854    -.0
> 676114                                                                       
>           .0816164
  100.001 a 400.000 habitantes  |  -.0043407   .0340661    -0.13   0.899     -.
> 071174                                                                       
>           .0624926
400.001 a 1.000.000 habitantes  |  -.0415836   .0379915    -1.09   0.274    -.1
> 161182                                                                       
>            .032951
   Más de 1.000.000 habitantes  |  -.1021446    .042834    -2.38   0.017    -.1
> 861794                                                                       
>          -.0181097
                                |
                           CCAA |
                        Aragón  |  -.0180744   .0361689    -0.50   0.617    -.0
> 890332                                                                       
>           .0528845
      Asturias (Principado de)  |   .0571927   .0546599     1.05   0.296    -.0
> 500431                                                                       
>           .1644285
               Balears (Illes)  |   .0566194   .0522332     1.08   0.279    -.0
> 458554                                                                       
>           .1590943
                      Canarias  |  -.0616406   .0347176    -1.78   0.076     -.
> 129752                                                                       
>           .0064709
                     Cantabria  |  -.0358813   .0367804    -0.98   0.329    -.1
> 080397                                                                       
>           .0362772
            Castilla-La Mancha  |   .1274481   .0597032     2.13   0.033     .0
> 103179                                                                       
>           .2445782
               Castilla y León  |   .0833806   .0554858     1.50   0.133    -.0
> 254755                                                                       
>           .1922367
                      Cataluña  |   .0107687   .0355197     0.30   0.762    -.0
> 589165                                                                       
>            .080454
          Comunitat Valenciana  |  -.0532832   .0276414    -1.93   0.054    -.1
> 075121                                                                       
>           .0009456
                   Extremadura  |  -.0213972   .0434415    -0.49   0.622    -.1
> 066239                                                                       
>           .0638295
                       Galicia  |  -.0937731   .0289587    -3.24   0.001    -.1
> 505864                                                                       
>          -.0369598
         Madrid (Comunidad de)  |   .0990361    .041773     2.37   0.018     .0
> 170827                                                                       
>           .1809894
  Navarra (Comunidad Foral de)  |  -.0162995   .0561382    -0.29   0.772    -.1
> 264354                                                                       
>           .0938365
                    País Vasco  |  -.0590737   .0366631    -1.61   0.107     -.
> 131002                                                                       
>           .0128547
                    Rioja (La)  |  -.0926714   .0265325    -3.49   0.000    -.1
> 447249                                                                       
>          -.0406179
    Ceuta (Ciudad Autónoma de)  |    .091289   .0812307     1.12   0.261    -.0
> 680753                                                                       
>           .2506532
  Melilla (Ciudad Autónoma de)  |  -.0314303   .0645777    -0.49   0.627    -.1
> 581235                                                                       
>            .095263
                                |
                          _cons |   .1518915   .1156009     1.31   0.189    -.0
> 749027                                                                       
>           .3786857
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,773
                                                F(3, 1769)        =       2.35
                                                Prob > F          =     0.0708
                                                R-squared         =     0.0057
                                                Root MSE          =     .30735

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0048955   .0156202    -0.31   0.754    -.0355315    .0
> 257405
           pp_dummy |  -.0259009   .0268877    -0.96   0.336    -.0786358    .0
> 268341
cabine_use_pp_dummy |   .1133558   .0451541     2.51   0.012     .0247948    .2
> 019169
              _cons |   .1034871   .0102273    10.12   0.000     .0834282    .1
> 235459
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,321
                                                F(44, 1276)       =       2.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0798
                                                Root MSE          =     .27944

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0241919   .0176312    -1.37   0.170    -.0
> 587811                                                                       
>           .0103974
                       pp_dummy |  -.0405929   .0298667    -1.36   0.174    -.0
> 991861                                                                       
>           .0180003
            cabine_use_pp_dummy |   .1123795   .0461255     2.44   0.015     .0
> 218894                                                                       
>           .2028696
                         female |   .0293014   .0158731     1.85   0.065    -.0
> 018388                                                                       
>           .0604417
                                |
                         income |
         Menos o igual a 300 €  |   .0238356   .0637444     0.37   0.709    -.1
> 012197                                                                       
>           .1488909
                De 301 a 600 €  |    .085634   .0415102     2.06   0.039     .0
> 041983                                                                       
>           .1670697
                De 601 a 900 €  |    .000789   .0301362     0.03   0.979    -.0
> 583329                                                                       
>           .0599109
              De 901 a 1.200 €  |   .0115994   .0287844     0.40   0.687    -.0
> 448707                                                                       
>           .0680694
            De 1.201 a 1.800 €  |    .005384    .028424     0.19   0.850    -.0
> 503789                                                                       
>            .061147
            De 1.801 a 2.400 €  |  -.0466234   .0296571    -1.57   0.116    -.1
> 048054                                                                       
>           .0115587
            De 2.401 a 3.000 €  |  -.0283647   .0443133    -0.64   0.522    -.1
> 152996                                                                       
>           .0585701
            De 3.001 a 4.500 €  |   .0693089   .0720478     0.96   0.336    -.0
> 720362                                                                       
>           .2106541
            De 4.501 a 6.000 €  |    -.08659   .0462554    -1.87   0.061    -.1
> 773349                                                                       
>           .0041549
                Más de 6.000 €  |  -.0768851   .0431292    -1.78   0.075    -.1
> 614969                                                                       
>           .0077268
                                |
                            age |  -.0012862   .0031814    -0.40   0.686    -.0
> 075276                                                                       
>           .0049553
                         age_sq |   .0000179   .0000337     0.53   0.595    -.0
> 000481                                                                       
>            .000084
                                |
                      education |
                      Primaria  |  -.0942125   .0956712    -0.98   0.325    -.2
> 819026                                                                       
>           .0934776
           Secundaria 1ª etapa  |  -.0515124   .0986148    -0.52   0.602    -.2
> 449774                                                                       
>           .1419526
           Secundaria 2ª etapa  |  -.0944746   .0989793    -0.95   0.340    -.2
> 886546                                                                       
>           .0997053
                          F.P.  |  -.0867195    .098514    -0.88   0.379    -.2
> 799867                                                                       
>           .1065476
                    Superiores  |  -.0760783   .0991532    -0.77   0.443    -.2
> 705994                                                                       
>           .1184429
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .044079   .0387434     1.14   0.255    -.0
> 319288                                                                       
>           .1200867
    10.001 a 50.000 habitantes  |   .0119326   .0346446     0.34   0.731     -.
> 056034                                                                       
>           .0798992
   50.001 a 100.000 habitantes  |  -.0037009   .0389332    -0.10   0.924     -.
> 080081                                                                       
>           .0726792
  100.001 a 400.000 habitantes  |  -.0148235   .0356598    -0.42   0.678    -.0
> 847818                                                                       
>           .0551347
400.001 a 1.000.000 habitantes  |  -.0501942   .0373556    -1.34   0.179    -.1
> 234794                                                                       
>           .0230911
   Más de 1.000.000 habitantes  |  -.1131607   .0437563    -2.59   0.010    -.1
> 990028                                                                       
>          -.0273186
                                |
                           CCAA |
                        Aragón  |  -.0230308   .0358186    -0.64   0.520    -.0
> 933006                                                                       
>            .047239
      Asturias (Principado de)  |   .0547412   .0542351     1.01   0.313    -.0
> 516586                                                                       
>           .1611409
               Balears (Illes)  |   .0502345   .0514238     0.98   0.329    -.0
> 506499                                                                       
>           .1511189
                      Canarias  |   -.059533    .034299    -1.74   0.083    -.1
> 268215                                                                       
>           .0077556
                     Cantabria  |  -.0369655   .0366606    -1.01   0.313    -.1
> 088872                                                                       
>           .0349563
            Castilla-La Mancha  |   .1257387   .0597891     2.10   0.036      .
> 008443                                                                       
>           .2430344
               Castilla y León  |   .0844092   .0554483     1.52   0.128    -.0
> 243707                                                                       
>           .1931891
                      Cataluña  |   .0046277   .0350957     0.13   0.895    -.0
> 642239                                                                       
>           .0734794
          Comunitat Valenciana  |  -.0561164   .0275656    -2.04   0.042    -.1
> 101953                                                                       
>          -.0020375
                   Extremadura  |   -.021425   .0433419    -0.49   0.621    -.1
> 064542                                                                       
>           .0636043
                       Galicia  |  -.0941525   .0286724    -3.28   0.001    -.1
> 504028                                                                       
>          -.0379023
         Madrid (Comunidad de)  |   .0923172   .0414563     2.23   0.026     .0
> 109871                                                                       
>           .1736472
            Murcia (Región de)  |  -.0635175   .0247194    -2.57   0.010    -.1
> 120126                                                                       
>          -.0150224
                    País Vasco  |  -.0621982   .0363017    -1.71   0.087    -.1
> 334158                                                                       
>           .0090193
                    Rioja (La)  |   -.095166   .0257793    -3.69   0.000    -.1
> 457404                                                                       
>          -.0445916
    Ceuta (Ciudad Autónoma de)  |   .0929423   .0812834     1.14   0.253    -.0
> 665215                                                                       
>           .2524062
  Melilla (Ciudad Autónoma de)  |  -.0312354     .06488    -0.48   0.630    -.1
> 585187                                                                       
>           .0960478
                                |
                          _cons |   .1769431   .1132696     1.56   0.119     -.
> 045272                                                                       
>           .3991581
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,806
                                                F(3, 1802)        =       2.21
                                                Prob > F          =     0.0850
                                                R-squared         =     0.0052
                                                Root MSE          =     .30132

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0102145   .0150949    -0.68   0.499    -.0398198    .0
> 193908
           pp_dummy |  -.0242005    .026657    -0.91   0.364    -.0764823    .0
> 280813
cabine_use_pp_dummy |   .1059533    .043198     2.45   0.014     .0212298    .1
> 906768
              _cons |   .1011236   .0101173    10.00   0.000     .0812808    .1
> 209664
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,317
                                                F(44, 1272)       =       2.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0773
                                                Root MSE          =     .28233

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0136829   .0179899    -0.76   0.447    -.0
> 489761                                                                       
>           .0216103
                       pp_dummy |  -.0385222   .0296884    -1.30   0.195    -.0
> 967659                                                                       
>           .0197214
            cabine_use_pp_dummy |   .1065544   .0463203     2.30   0.022     .0
> 156819                                                                       
>           .1974269
                         female |   .0319307   .0162009     1.97   0.049     .0
> 001474                                                                       
>           .0637141
                                |
                         income |
         Menos o igual a 300 €  |   .0243559   .0637828     0.38   0.703    -.1
> 007752                                                                       
>           .1494871
                De 301 a 600 €  |   .0848633   .0418114     2.03   0.043     .0
> 028364                                                                       
>           .1668902
                De 601 a 900 €  |   .0066061   .0311115     0.21   0.832    -.0
> 544294                                                                       
>           .0676415
              De 901 a 1.200 €  |    .012345   .0288762     0.43   0.669    -.0
> 443052                                                                       
>           .0689952
            De 1.201 a 1.800 €  |   .0085907   .0288669     0.30   0.766    -.0
> 480413                                                                       
>           .0652226
            De 1.801 a 2.400 €  |  -.0377159   .0312149    -1.21   0.227    -.0
> 989543                                                                       
>           .0235225
            De 2.401 a 3.000 €  |  -.0259643   .0437266    -0.59   0.553    -.1
> 117485                                                                       
>           .0598199
            De 3.001 a 4.500 €  |   .0630125   .0676077     0.93   0.351    -.0
> 696224                                                                       
>           .1956474
            De 4.501 a 6.000 €  |  -.0766397   .0481566    -1.59   0.112    -.1
> 711148                                                                       
>           .0178353
                Más de 6.000 €  |  -.0768351   .0419888    -1.83   0.067      -
> .15921                                                                       
>           .0055398
                                |
                            age |  -.0014807   .0032653    -0.45   0.650    -.0
> 078867                                                                       
>           .0049252
                         age_sq |   .0000203   .0000347     0.59   0.558    -.0
> 000478                                                                       
>           .0000884
                                |
                      education |
                      Primaria  |  -.0875883    .091861    -0.95   0.341    -.2
> 678041                                                                       
>           .0926274
           Secundaria 1ª etapa  |  -.0404194   .0948393    -0.43   0.670    -.2
> 264781                                                                       
>           .1456392
           Secundaria 2ª etapa  |  -.0892989   .0950481    -0.94   0.348    -.2
> 757672                                                                       
>           .0971694
                          F.P.  |  -.0770696   .0945011    -0.82   0.415    -.2
> 624647                                                                       
>           .1083256
                    Superiores  |  -.0734202   .0951257    -0.77   0.440    -.2
> 600408                                                                       
>           .1132003
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0681072   .0360862     1.89   0.059    -.0
> 026879                                                                       
>           .1389022
    10.001 a 50.000 habitantes  |   .0318537   .0312282     1.02   0.308    -.0
> 294108                                                                       
>           .0931182
   50.001 a 100.000 habitantes  |   .0189307   .0366298     0.52   0.605    -.0
> 529309                                                                       
>           .0907922
  100.001 a 400.000 habitantes  |   .0049474   .0321127     0.15   0.878    -.0
> 580522                                                                       
>            .067947
400.001 a 1.000.000 habitantes  |  -.0272385   .0348567    -0.78   0.435    -.0
> 956213                                                                       
>           .0411444
   Más de 1.000.000 habitantes  |  -.0928387   .0414721    -2.24   0.025       
> -.1742                                                                       
>          -.0114774
                                |
                           CCAA |
                        Aragón  |    -.01913   .0356918    -0.54   0.592    -.0
> 891513                                                                       
>           .0508913
      Asturias (Principado de)  |   .0569781   .0542541     1.05   0.294    -.0
> 494593                                                                       
>           .1634154
               Balears (Illes)  |   .0531432   .0515719     1.03   0.303    -.0
> 480322                                                                       
>           .1543185
                      Canarias  |  -.0633596   .0343761    -1.84   0.066    -.1
> 307998                                                                       
>           .0040805
                     Cantabria  |   -.033827    .036483    -0.93   0.354    -.1
> 054004                                                                       
>           .0377465
            Castilla-La Mancha  |   .1255777   .0597064     2.10   0.036     .0
> 084438                                                                       
>           .2427116
               Castilla y León  |   .0866265   .0555378     1.56   0.119    -.0
> 223292                                                                       
>           .1955822
                      Cataluña  |   .0103515   .0352113     0.29   0.769     -.
> 058727                                                                       
>             .07943
          Comunitat Valenciana  |  -.0548705   .0276341    -1.99   0.047    -.1
> 090839                                                                       
>           -.000657
                   Extremadura  |  -.0189317   .0431784    -0.44   0.661    -.1
> 036404                                                                       
>            .065777
                       Galicia  |  -.0935025   .0285864    -3.27   0.001    -.1
> 495841                                                                       
>          -.0374208
         Madrid (Comunidad de)  |   .0976881   .0415757     2.35   0.019     .0
> 161236                                                                       
>           .1792525
            Murcia (Región de)  |  -.0645237   .0247189    -2.61   0.009    -.1
> 130179                                                                       
>          -.0160294
  Navarra (Comunidad Foral de)  |  -.0144509   .0559588    -0.26   0.796    -.1
> 242326                                                                       
>           .0953309
                    Rioja (La)  |    -.09053   .0260384    -3.48   0.001     -.
> 141613                                                                       
>          -.0394471
    Ceuta (Ciudad Autónoma de)  |   .0888838   .0812328     1.09   0.274    -.0
> 704813                                                                       
>           .2482488
  Melilla (Ciudad Autónoma de)  |  -.0332454   .0649121    -0.51   0.609    -.1
> 605919                                                                       
>           .0941011
                                |
                          _cons |   .1426025   .1113406     1.28   0.201    -.0
> 758289                                                                       
>           .3610338
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,789
                                                F(3, 1785)        =       2.11
                                                Prob > F          =     0.0972
                                                R-squared         =     0.0048
                                                Root MSE          =     .30555

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0071965   .0154669    -0.47   0.642    -.0375316    .0
> 231387
           pp_dummy |  -.0272555   .0265373    -1.03   0.305    -.0793029    .0
> 247918
cabine_use_pp_dummy |   .1048383   .0433708     2.42   0.016     .0197754    .1
> 899013
              _cons |   .1035267   .0102869    10.06   0.000      .083351    .1
> 237025
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,331
                                                F(44, 1286)       =       2.09
                                                Prob > F          =     0.0001
                                                R-squared         =     0.0756
                                                Root MSE          =     .28224

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0158507   .0177876    -0.89   0.373    -.0
> 507465                                                                       
>           .0190451
                       pp_dummy |  -.0419932   .0307172    -1.37   0.172    -.1
> 022546                                                                       
>           .0182682
            cabine_use_pp_dummy |   .1110319   .0476835     2.33   0.020     .0
> 174859                                                                       
>           .2045779
                         female |   .0293699     .01614     1.82   0.069    -.0
> 022936                                                                       
>           .0610335
                                |
                         income |
         Menos o igual a 300 €  |   .0256055    .063892     0.40   0.689    -.0
> 997385                                                                       
>           .1509495
                De 301 a 600 €  |   .0830768   .0415565     2.00   0.046     .0
> 015508                                                                       
>           .1646029
                De 601 a 900 €  |   .0108512   .0308312     0.35   0.725    -.0
> 496337                                                                       
>           .0713361
              De 901 a 1.200 €  |   .0123564    .028762     0.43   0.668    -.0
> 440691                                                                       
>           .0687819
            De 1.201 a 1.800 €  |   .0072951   .0284592     0.26   0.798    -.0
> 485365                                                                       
>           .0631267
            De 1.801 a 2.400 €  |  -.0364006   .0309322    -1.18   0.239    -.0
> 970837                                                                       
>           .0242826
            De 2.401 a 3.000 €  |  -.0242171    .043258    -0.56   0.576    -.1
> 090811                                                                       
>           .0606469
            De 3.001 a 4.500 €  |   .0683137   .0725001     0.94   0.346    -.0
> 739177                                                                       
>            .210545
            De 4.501 a 6.000 €  |   -.074544   .0482296    -1.55   0.122    -.1
> 691613                                                                       
>           .0200733
                Más de 6.000 €  |  -.0729828   .0423196    -1.72   0.085    -.1
> 560059                                                                       
>           .0100403
                                |
                            age |  -.0012963   .0031812    -0.41   0.684    -.0
> 075372                                                                       
>           .0049446
                         age_sq |   .0000178   .0000337     0.53   0.598    -.0
> 000484                                                                       
>            .000084
                                |
                      education |
                      Primaria  |  -.0804336   .0923963    -0.87   0.384    -.2
> 616976                                                                       
>           .1008304
           Secundaria 1ª etapa  |  -.0422664   .0949042    -0.45   0.656    -.2
> 284505                                                                       
>           .1439176
           Secundaria 2ª etapa  |  -.0896572   .0952477    -0.94   0.347    -.2
> 765152                                                                       
>           .0972007
                          F.P.  |    -.08011   .0946597    -0.85   0.398    -.2
> 658144                                                                       
>           .1055943
                    Superiores  |  -.0752908   .0953057    -0.79   0.430    -.2
> 622624                                                                       
>           .1116809
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |    .054169   .0380386     1.42   0.155    -.0
> 204556                                                                       
>           .1287935
    10.001 a 50.000 habitantes  |   .0189495   .0336408     0.56   0.573    -.0
> 470474                                                                       
>           .0849463
   50.001 a 100.000 habitantes  |   .0047217   .0384548     0.12   0.902    -.0
> 707193                                                                       
>           .0801626
  100.001 a 400.000 habitantes  |  -.0093787   .0353685    -0.27   0.791     -.
> 078765                                                                       
>           .0600075
400.001 a 1.000.000 habitantes  |  -.0398388   .0369843    -1.08   0.282     -.
> 112395                                                                       
>           .0327174
   Más de 1.000.000 habitantes  |  -.1055114   .0436017    -2.42   0.016    -.1
> 910496                                                                       
>          -.0199732
                                |
                           CCAA |
                        Aragón  |  -.0226207   .0358264    -0.63   0.528    -.0
> 929052                                                                       
>           .0476639
      Asturias (Principado de)  |   .0569293   .0542518     1.05   0.294    -.0
> 495024                                                                       
>            .163361
               Balears (Illes)  |   .0524283   .0516884     1.01   0.311    -.0
> 489746                                                                       
>           .1538313
                      Canarias  |  -.0621642   .0344139    -1.81   0.071    -.1
> 296777                                                                       
>           .0053494
                     Cantabria  |  -.0356353   .0365829    -0.97   0.330    -.1
> 074039                                                                       
>           .0361334
            Castilla-La Mancha  |   .1263639   .0597019     2.12   0.034       
> .00924                                                                       
>           .2434877
               Castilla y León  |   .0844784   .0553261     1.53   0.127    -.0
> 240609                                                                       
>           .1930177
                      Cataluña  |   .0090581    .035215     0.26   0.797     -.
> 060027                                                                       
>           .0781433
          Comunitat Valenciana  |  -.0549705   .0276264    -1.99   0.047    -.1
> 091682                                                                       
>          -.0007727
                   Extremadura  |  -.0209093   .0433316    -0.48   0.630    -.1
> 059176                                                                       
>            .064099
                       Galicia  |  -.0932248   .0285608    -3.26   0.001    -.1
> 492557                                                                       
>          -.0371938
         Madrid (Comunidad de)  |   .0979627   .0415287     2.36   0.018     .0
> 164913                                                                       
>           .1794341
            Murcia (Región de)  |  -.0644555   .0247309    -2.61   0.009    -.1
> 129728                                                                       
>          -.0159382
  Navarra (Comunidad Foral de)  |  -.0162504   .0559122    -0.29   0.771    -.1
> 259395                                                                       
>           .0934386
                    País Vasco  |  -.0598328    .036266    -1.65   0.099    -.1
> 309799                                                                       
>           .0113143
    Ceuta (Ciudad Autónoma de)  |   .0921996   .0811716     1.14   0.256    -.0
> 670437                                                                       
>            .251443
  Melilla (Ciudad Autónoma de)  |  -.0326992   .0645443    -0.51   0.613    -.1
> 593229                                                                       
>           .0939246
                                |
                          _cons |   .1561031   .1115148     1.40   0.162    -.0
> 626679                                                                       
>           .3748741
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,787
                                                F(3, 1783)        =       1.81
                                                Prob > F          =     0.1424
                                                R-squared         =     0.0042
                                                Root MSE          =     .30361

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |   -.009235   .0152853    -0.60   0.546    -.0392139    .0
> 207439
           pp_dummy |  -.0217122   .0278571    -0.78   0.436    -.0763482    .0
> 329238
cabine_use_pp_dummy |   .0986966   .0447818     2.20   0.028     .0108662    .1
> 865269
              _cons |   .1027933   .0101626    10.11   0.000     .0828615    .1
> 227251
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,330
                                                F(44, 1285)       =       2.27
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0750
                                                Root MSE          =     .27716

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0200637   .0174805    -1.15   0.251    -.0
> 543572                                                                       
>           .0142297
                       pp_dummy |    -.03919   .0296491    -1.32   0.186     -.
> 097356                                                                       
>            .018976
            cabine_use_pp_dummy |   .1038637   .0461142     2.25   0.024     .0
> 133963                                                                       
>            .194331
                         female |   .0263639   .0158214     1.67   0.096    -.0
> 046748                                                                       
>           .0574026
                                |
                         income |
         Menos o igual a 300 €  |   .0306859   .0634996     0.48   0.629    -.0
> 938883                                                                       
>           .1552601
                De 301 a 600 €  |   .0792721   .0402076     1.97   0.049     .0
> 003923                                                                       
>           .1581518
                De 601 a 900 €  |   .0139165    .030381     0.46   0.647    -.0
> 456853                                                                       
>           .0735183
              De 901 a 1.200 €  |   .0151413   .0280232     0.54   0.589    -.0
> 398349                                                                       
>           .0701175
            De 1.201 a 1.800 €  |   .0159882   .0281088     0.57   0.570    -.0
> 391559                                                                       
>           .0711322
            De 1.801 a 2.400 €  |  -.0311289   .0303898    -1.02   0.306    -.0
> 907481                                                                       
>           .0284902
            De 2.401 a 3.000 €  |  -.0220178   .0425386    -0.52   0.605    -.1
> 054705                                                                       
>           .0614349
            De 3.001 a 4.500 €  |   .0663316   .0672342     0.99   0.324    -.0
> 655692                                                                       
>           .1982323
            De 4.501 a 6.000 €  |  -.0747295   .0459884    -1.62   0.104    -.1
> 649501                                                                       
>           .0154911
                Más de 6.000 €  |  -.0731641   .0422096    -1.73   0.083    -.1
> 559713                                                                       
>           .0096431
                                |
                            age |  -.0018231   .0031635    -0.58   0.565    -.0
> 080292                                                                       
>           .0043831
                         age_sq |   .0000233   .0000338     0.69   0.490    -.0
> 000429                                                                       
>           .0000895
                                |
                      education |
                      Primaria  |  -.0788708   .0922264    -0.86   0.393    -.2
> 598017                                                                       
>           .1020602
           Secundaria 1ª etapa  |  -.0443472   .0946121    -0.47   0.639    -.2
> 299584                                                                       
>           .1412639
           Secundaria 2ª etapa  |  -.0935524   .0948455    -0.99   0.324    -.2
> 796213                                                                       
>           .0925166
                          F.P.  |  -.0749473   .0944703    -0.79   0.428    -.2
> 602802                                                                       
>           .1103856
                    Superiores  |  -.0723535   .0951033    -0.76   0.447    -.2
> 589283                                                                       
>           .1142213
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0541617   .0370265     1.46   0.144    -.0
> 184773                                                                       
>           .1268007
    10.001 a 50.000 habitantes  |   .0181361   .0326786     0.55   0.579    -.0
> 459732                                                                       
>           .0822454
   50.001 a 100.000 habitantes  |   .0041038   .0377105     0.11   0.913     -.
> 069877                                                                       
>           .0780847
  100.001 a 400.000 habitantes  |  -.0097107   .0338073    -0.29   0.774    -.0
> 760343                                                                       
>            .056613
400.001 a 1.000.000 habitantes  |  -.0419012   .0360741    -1.16   0.246    -.1
> 126717                                                                       
>           .0288693
   Más de 1.000.000 habitantes  |  -.1083422   .0427297    -2.54   0.011    -.1
> 921699                                                                       
>          -.0245145
                                |
                           CCAA |
                        Aragón  |   -.024417   .0357134    -0.68   0.494      -
> .09448                                                                       
>            .045646
      Asturias (Principado de)  |   .0539992   .0544539     0.99   0.322    -.0
> 528291                                                                       
>           .1608274
               Balears (Illes)  |   .0500671   .0516579     0.97   0.333     -.
> 051276                                                                       
>           .1514102
                      Canarias  |  -.0611164   .0342176    -1.79   0.074    -.1
> 282449                                                                       
>            .006012
                     Cantabria  |  -.0380791   .0365634    -1.04   0.298    -.1
> 098095                                                                       
>           .0336514
            Castilla-La Mancha  |   .1248995   .0598021     2.09   0.037     .0
> 075789                                                                       
>             .24222
               Castilla y León  |   .0827856   .0554232     1.49   0.135    -.0
> 259443                                                                       
>           .1915155
                      Cataluña  |   .0051392   .0350535     0.15   0.883    -.0
> 636292                                                                       
>           .0739076
          Comunitat Valenciana  |  -.0559411   .0275256    -2.03   0.042    -.1
> 099411                                                                       
>          -.0019411
                   Extremadura  |  -.0199439   .0431411    -0.46   0.644    -.1
> 045786                                                                       
>           .0646907
                       Galicia  |  -.0934547   .0284835    -3.28   0.001    -.1
> 493341                                                                       
>          -.0375753
         Madrid (Comunidad de)  |   .0947956   .0415327     2.28   0.023     .0
> 133162                                                                       
>            .176275
            Murcia (Región de)  |  -.0651701   .0245524    -2.65   0.008    -.1
> 133373                                                                       
>          -.0170028
  Navarra (Comunidad Foral de)  |  -.0196337   .0558613    -0.35   0.725    -.1
> 292231                                                                       
>           .0899556
                    País Vasco  |  -.0644422   .0361406    -1.78   0.075    -.1
> 353434                                                                       
>           .0064589
                    Rioja (La)  |  -.0910779    .025581    -3.56   0.000    -.1
> 412631                                                                       
>          -.0408927
  Melilla (Ciudad Autónoma de)  |  -.0315458   .0646535    -0.49   0.626    -.1
> 583839                                                                       
>           .0952923
                                |
                          _cons |   .1689127    .110123     1.53   0.125    -.0
> 471278                                                                       
>           .3849532
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,812
                                                F(3, 1808)        =       2.00
                                                Prob > F          =     0.1126
                                                R-squared         =     0.0044
                                                Root MSE          =     .30099

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |    -.01271   .0150646    -0.84   0.399    -.0422558    .0
> 168358
           pp_dummy |  -.0263778   .0264628    -1.00   0.319    -.0782788    .0
> 255231
cabine_use_pp_dummy |   .1031055   .0433572     2.38   0.018       .01807    .1
> 881409
              _cons |    .102649   .0100943    10.17   0.000     .0828514    .1
> 224466
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,339
                                                F(44, 1294)       =       2.35
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0771
                                                Root MSE          =     .28017

-------------------------------------------------------------------------------
------------------
                                |               Robust
                  uncomfortable | Coefficient  std. err.      t    P>|t|     [9
> 5% con                                                                       
>       f. interval]
--------------------------------+----------------------------------------------
------------------
                     cabine_use |  -.0183448   .0175216    -1.05   0.295    -.0
> 527186                                                                       
>           .0160291
                       pp_dummy |  -.0384647   .0299672    -1.28   0.200    -.0
> 972544                                                                       
>            .020325
            cabine_use_pp_dummy |   .1133787   .0470473     2.41   0.016     .0
> 210814                                                                       
>            .205676
                         female |   .0311622   .0159121     1.96   0.050    -.0
> 000541                                                                       
>           .0623786
                                |
                         income |
         Menos o igual a 300 €  |   .0300808   .0652583     0.46   0.645    -.0
> 979428                                                                       
>           .1581045
                De 301 a 600 €  |   .0721283   .0400744     1.80   0.072    -.0
> 064896                                                                       
>           .1507462
                De 601 a 900 €  |    .010969   .0307556     0.36   0.721    -.0
> 493673                                                                       
>           .0713053
              De 901 a 1.200 €  |   .0136533   .0285474     0.48   0.633     -.
> 042351                                                                       
>           .0696575
            De 1.201 a 1.800 €  |   .0074239   .0280575     0.26   0.791    -.0
> 476193                                                                       
>           .0624671
            De 1.801 a 2.400 €  |  -.0359799   .0305685    -1.18   0.239    -.0
> 959492                                                                       
>           .0239894
            De 2.401 a 3.000 €  |  -.0253633   .0426416    -0.59   0.552    -.1
> 090176                                                                       
>           .0582911
            De 3.001 a 4.500 €  |   .0633382   .0674992     0.94   0.348    -.0
> 690816                                                                       
>            .195758
            De 4.501 a 6.000 €  |  -.0766968   .0478098    -1.60   0.109    -.1
> 704901                                                                       
>           .0170964
                Más de 6.000 €  |  -.0733296   .0423627    -1.73   0.084    -.1
> 564367                                                                       
>           .0097776
                                |
                            age |  -.0013966   .0031494    -0.44   0.658     -.
> 007575                                                                       
>           .0047818
                         age_sq |   .0000186   .0000334     0.56   0.578     -.
> 000047                                                                       
>           .0000841
                                |
                      education |
                      Primaria  |  -.0877123   .0923406    -0.95   0.342     -.
> 268866                                                                       
>           .0934413
           Secundaria 1ª etapa  |  -.0418042   .0948906    -0.44   0.660    -.2
> 279605                                                                       
>            .144352
           Secundaria 2ª etapa  |  -.0897669   .0952645    -0.94   0.346    -.2
> 766567                                                                       
>           .0971229
                          F.P.  |  -.0801297   .0947682    -0.85   0.398    -.2
> 660459                                                                       
>           .1057866
                    Superiores  |  -.0751099   .0953992    -0.79   0.431     -.
> 262264                                                                       
>           .1120442
                                |
                         TAMUNI |
     2.001 a 10.000 habitantes  |   .0534308   .0370467     1.44   0.149    -.0
> 192474                                                                       
>            .126109
    10.001 a 50.000 habitantes  |   .0181848   .0327067     0.56   0.578    -.0
> 459793                                                                       
>           .0823488
   50.001 a 100.000 habitantes  |   .0041236   .0377308     0.11   0.913    -.0
> 698967                                                                       
>           .0781438
  100.001 a 400.000 habitantes  |  -.0089218   .0338759    -0.26   0.792    -.0
> 753794                                                                       
>           .0575358
400.001 a 1.000.000 habitantes  |  -.0411764    .036089    -1.14   0.254    -.1
> 119758                                                                       
>            .029623
   Más de 1.000.000 habitantes  |  -.1061396   .0427908    -2.48   0.013    -.1
> 900865                                                                       
>          -.0221926
                                |
                           CCAA |
                        Aragón  |  -.0226798   .0356533    -0.64   0.525    -.0
> 926243                                                                       
>           .0472647
      Asturias (Principado de)  |   .0555926   .0541499     1.03   0.305    -.0
> 506386                                                                       
>           .1618239
               Balears (Illes)  |   .0519255   .0515653     1.01   0.314    -.0
> 492352                                                                       
>           .1530862
                      Canarias  |  -.0616985   .0342666    -1.80   0.072    -.1
> 289226                                                                       
>           .0055257
                     Cantabria  |  -.0360148   .0366573    -0.98   0.326     -.
> 107929                                                                       
>           .0358994
            Castilla-La Mancha  |   .1243095   .0596034     2.09   0.037     .0
> 073797                                                                       
>           .2412393
               Castilla y León  |     .08527   .0554282     1.54   0.124     -.
> 023469                                                                       
>           .1940091
                      Cataluña  |   .0081064   .0351607     0.23   0.818    -.0
> 608717                                                                       
>           .0770846
          Comunitat Valenciana  |  -.0548594   .0275512    -1.99   0.047    -.1
> 089093                                                                       
>          -.0008096
                   Extremadura  |  -.0205087   .0433248    -0.47   0.636    -.1
> 055033                                                                       
>           .0644859
                       Galicia  |  -.0927203   .0284846    -3.26   0.001    -.1
> 486014                                                                       
>          -.0368392
         Madrid (Comunidad de)  |   .0959428   .0415143     2.31   0.021     .0
> 145002                                                                       
>           .1773855
            Murcia (Región de)  |  -.0648615   .0246326    -2.63   0.009    -.1
> 131857                                                                       
>          -.0165372
  Navarra (Comunidad Foral de)  |  -.0155878   .0559227    -0.28   0.780    -.1
> 252969                                                                       
>           .0941214
                    País Vasco  |   -.060398   .0363261    -1.66   0.097    -.1
> 316625                                                                       
>           .0108665
                    Rioja (La)  |  -.0924871   .0257756    -3.59   0.000    -.1
> 430537                                                                       
>          -.0419204
    Ceuta (Ciudad Autónoma de)  |   .0907419   .0812237     1.12   0.264    -.0
> 686027                                                                       
>           .2500865
                                |
                          _cons |   .1605457   .1108972     1.45   0.148    -.0
> 570122                                                                       
>           .3781036
-------------------------------------------------------------------------------
------------------
(variable Controls was str13, now str16 to accommodate using data's values)
file 01_data/survey_ccaa_jk_2.dta saved

Linear regression                               Number of obs     =      1,830
                                                F(3, 1826)        =       2.32
                                                Prob > F          =     0.0731
                                                R-squared         =     0.0054
                                                Root MSE          =     .30312

-------------------------------------------------------------------------------
------
                    |               Robust
      uncomfortable | Coefficient  std. err.      t    P>|t|     [95% conf. int
> erval]
--------------------+----------------------------------------------------------
------
         cabine_use |  -.0101364   .0150643    -0.67   0.501    -.0396816    .0
> 194087
           pp_dummy |  -.0256128   .0266439    -0.96   0.337    -.0778685     .
> 026643
cabine_use_pp_dummy |   .1109911   .0438211     2.53   0.011     .0250465    .1
> 969358
              _cons |   .1025358   .0100837    10.17   0.000     .0827591    .1
> 223125
-------------------------------------------------------------------------------
------
file 01_data/survey_ccaa_jk_2.dta saved

. 
end of do-file

. do "/var/folders/hn/8ndnrl6x72b8nlkz08gtc0mr0000gn/T//SD50600.000000"

. log close
      name:  <unnamed>
       log:  /Users/vicentevalentim/Dropbox/JOP third submission/JOP replicatio
> n/cabinas_jop_log.smcl
  log type:  smcl
 closed on:  19 Sep 2023, 12:41:43
-------------------------------------------------------------------------------
